#technical-writing — Public Fediverse posts

The truth is that LLMs are mostly unpredictable and, as such, you can’t rely on AI agents to strictly follow the instructions stored in a markdown file. Even when they execute all the instructions contained in the skills, they often leave a backtrail full of trash/dirt. Because they’re often unruly, they need another chatbot to put them in line, as well as a human in the loop, of course. Basically, it’s a lot of trial and error…

“I acknowledge that “programming an LLM” is putting it optimistically, as skills aren’t usually deterministic scripts. But I like to think of them this way, and keep refining the skill until it yields the consistent result that I want.
Overall, I’m persuaded that tech writers who can build successful skills to automate their tasks will be on their way to the 10x tech writer goal (if that’s your aim). The best way tech writers can free up their time is by creating skills to attack those repeatable tasks (like release notes) since repeatable tasks keep chipping away at our productivity week after week. If you can fashion a skill that handles those recurring tasks, then you free up a recurring amount of bandwidth each week.

Additionally, most repeatable tasks fall into the category of mechanical toil that we want to automate with AI anyway. If we can automate the repeatable tasks, then we’ll have more time to tackle the one-off complex tasks that don’t fall into our laps weekly or biweekly.”

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #LLMs #AIAgents #AgenticAI #Skills #TechnicalWriting #SoftwareDocumentation

The truth is that LLMs are mostly unpredictable and, as such, you can’t rely on AI agents to strictly follow the instructions stored in a markdown file. Even when they execute all the instructions contained in the skills, they often leave a backtrail full of trash/dirt. Because they’re often unruly, they need another chatbot to put them in line, as well as a human in the loop, of course. Basically, it’s a lot of trial and error…

“I acknowledge that “programming an LLM” is putting it optimistically, as skills aren’t usually deterministic scripts. But I like to think of them this way, and keep refining the skill until it yields the consistent result that I want.
Overall, I’m persuaded that tech writers who can build successful skills to automate their tasks will be on their way to the 10x tech writer goal (if that’s your aim). The best way tech writers can free up their time is by creating skills to attack those repeatable tasks (like release notes) since repeatable tasks keep chipping away at our productivity week after week. If you can fashion a skill that handles those recurring tasks, then you free up a recurring amount of bandwidth each week.

Additionally, most repeatable tasks fall into the category of mechanical toil that we want to automate with AI anyway. If we can automate the repeatable tasks, then we’ll have more time to tackle the one-off complex tasks that don’t fall into our laps weekly or biweekly.”

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #LLMs #AIAgents #AgenticAI #Skills #TechnicalWriting #SoftwareDocumentation

The truth is that LLMs are mostly unpredictable and, as such, you can’t rely on AI agents to strictly follow the instructions stored in a markdown file. Even when they execute all the instructions contained in the skills, they often leave a backtrail full of trash/dirt. Because they’re often unruly, they need another chatbot to put them in line, as well as a human in the loop, of course. Basically, it’s a lot of trial and error…

“I acknowledge that “programming an LLM” is putting it optimistically, as skills aren’t usually deterministic scripts. But I like to think of them this way, and keep refining the skill until it yields the consistent result that I want.
Overall, I’m persuaded that tech writers who can build successful skills to automate their tasks will be on their way to the 10x tech writer goal (if that’s your aim). The best way tech writers can free up their time is by creating skills to attack those repeatable tasks (like release notes) since repeatable tasks keep chipping away at our productivity week after week. If you can fashion a skill that handles those recurring tasks, then you free up a recurring amount of bandwidth each week.

Additionally, most repeatable tasks fall into the category of mechanical toil that we want to automate with AI anyway. If we can automate the repeatable tasks, then we’ll have more time to tackle the one-off complex tasks that don’t fall into our laps weekly or biweekly.”

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #LLMs #AIAgents #AgenticAI #Skills #TechnicalWriting #SoftwareDocumentation

The truth is that LLMs are mostly unpredictable and, as such, you can’t rely on AI agents to strictly follow the instructions stored in a markdown file. Even when they execute all the instructions contained in the skills, they often leave a backtrail full of trash/dirt. Because they’re often unruly, they need another chatbot to put them in line, as well as a human in the loop, of course. Basically, it’s a lot of trial and error…

“I acknowledge that “programming an LLM” is putting it optimistically, as skills aren’t usually deterministic scripts. But I like to think of them this way, and keep refining the skill until it yields the consistent result that I want.
Overall, I’m persuaded that tech writers who can build successful skills to automate their tasks will be on their way to the 10x tech writer goal (if that’s your aim). The best way tech writers can free up their time is by creating skills to attack those repeatable tasks (like release notes) since repeatable tasks keep chipping away at our productivity week after week. If you can fashion a skill that handles those recurring tasks, then you free up a recurring amount of bandwidth each week.

Additionally, most repeatable tasks fall into the category of mechanical toil that we want to automate with AI anyway. If we can automate the repeatable tasks, then we’ll have more time to tackle the one-off complex tasks that don’t fall into our laps weekly or biweekly.”

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #LLMs #AIAgents #AgenticAI #Skills #TechnicalWriting #SoftwareDocumentation

The truth is that LLMs are mostly unpredictable and, as such, you can’t rely on AI agents to strictly follow the instructions stored in a markdown file. Even when they execute all the instructions contained in the skills, they often leave a backtrail full of trash/dirt. Because they’re often unruly, they need another chatbot to put them in line, as well as a human in the loop, of course. Basically, it’s a lot of trial and error…

“I acknowledge that “programming an LLM” is putting it optimistically, as skills aren’t usually deterministic scripts. But I like to think of them this way, and keep refining the skill until it yields the consistent result that I want.
Overall, I’m persuaded that tech writers who can build successful skills to automate their tasks will be on their way to the 10x tech writer goal (if that’s your aim). The best way tech writers can free up their time is by creating skills to attack those repeatable tasks (like release notes) since repeatable tasks keep chipping away at our productivity week after week. If you can fashion a skill that handles those recurring tasks, then you free up a recurring amount of bandwidth each week.

Additionally, most repeatable tasks fall into the category of mechanical toil that we want to automate with AI anyway. If we can automate the repeatable tasks, then we’ll have more time to tackle the one-off complex tasks that don’t fall into our laps weekly or biweekly.”

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #LLMs #AIAgents #AgenticAI #Skills #TechnicalWriting #SoftwareDocumentation

Here’s why contextual and use case-based documentation matters a lot when it comes to APIs:

“The problem is that documentation is often organized entirely around individual endpoints with very little cross-endpoint guidance, implicit prerequisites, or multi-step call documentation. For this reason, API use often involves tribal knowledge held by the average human operator.

A better way to organize this, or perhaps a complementary way, is to create documentation around workflows and common scenarios. You don't have to document every single potential interaction. In many cases, simply documenting common use cases and then delineating what they share is more than enough for the agentic systems to infer how the API actually functions in practice. This, alongside additional deterministic context, will help agents understand your systems in a human-like context without having to have a human on the other side of the request.

The goal: Provide documentation not just of individual endpoints but of the collective flow between them, allowing agents to understand your service properly.”

https://nordicapis.com/10-factors-for-checking-your-apis-ai-readiness/

#API #APIs #APIDocumentation #AI #AIAgents #TechnicalWriting #SoftwareDocumentation #APIDesign

Here’s why contextual and use case-based documentation matters a lot when it comes to APIs:

“The problem is that documentation is often organized entirely around individual endpoints with very little cross-endpoint guidance, implicit prerequisites, or multi-step call documentation. For this reason, API use often involves tribal knowledge held by the average human operator.

A better way to organize this, or perhaps a complementary way, is to create documentation around workflows and common scenarios. You don't have to document every single potential interaction. In many cases, simply documenting common use cases and then delineating what they share is more than enough for the agentic systems to infer how the API actually functions in practice. This, alongside additional deterministic context, will help agents understand your systems in a human-like context without having to have a human on the other side of the request.

The goal: Provide documentation not just of individual endpoints but of the collective flow between them, allowing agents to understand your service properly.”

https://nordicapis.com/10-factors-for-checking-your-apis-ai-readiness/

#API #APIs #APIDocumentation #AI #AIAgents #TechnicalWriting #SoftwareDocumentation #APIDesign

Here’s why contextual and use case-based documentation matters a lot when it comes to APIs:

“The problem is that documentation is often organized entirely around individual endpoints with very little cross-endpoint guidance, implicit prerequisites, or multi-step call documentation. For this reason, API use often involves tribal knowledge held by the average human operator.

A better way to organize this, or perhaps a complementary way, is to create documentation around workflows and common scenarios. You don't have to document every single potential interaction. In many cases, simply documenting common use cases and then delineating what they share is more than enough for the agentic systems to infer how the API actually functions in practice. This, alongside additional deterministic context, will help agents understand your systems in a human-like context without having to have a human on the other side of the request.

The goal: Provide documentation not just of individual endpoints but of the collective flow between them, allowing agents to understand your service properly.”

https://nordicapis.com/10-factors-for-checking-your-apis-ai-readiness/

#API #APIs #APIDocumentation #AI #AIAgents #TechnicalWriting #SoftwareDocumentation #APIDesign

Here’s why contextual and use case-based documentation matters a lot when it comes to APIs:

“The problem is that documentation is often organized entirely around individual endpoints with very little cross-endpoint guidance, implicit prerequisites, or multi-step call documentation. For this reason, API use often involves tribal knowledge held by the average human operator.

A better way to organize this, or perhaps a complementary way, is to create documentation around workflows and common scenarios. You don't have to document every single potential interaction. In many cases, simply documenting common use cases and then delineating what they share is more than enough for the agentic systems to infer how the API actually functions in practice. This, alongside additional deterministic context, will help agents understand your systems in a human-like context without having to have a human on the other side of the request.

The goal: Provide documentation not just of individual endpoints but of the collective flow between them, allowing agents to understand your service properly.”

https://nordicapis.com/10-factors-for-checking-your-apis-ai-readiness/

#API #APIs #APIDocumentation #AI #AIAgents #TechnicalWriting #SoftwareDocumentation #APIDesign

Here’s why contextual and use case-based documentation matters a lot when it comes to APIs:

“The problem is that documentation is often organized entirely around individual endpoints with very little cross-endpoint guidance, implicit prerequisites, or multi-step call documentation. For this reason, API use often involves tribal knowledge held by the average human operator.

A better way to organize this, or perhaps a complementary way, is to create documentation around workflows and common scenarios. You don't have to document every single potential interaction. In many cases, simply documenting common use cases and then delineating what they share is more than enough for the agentic systems to infer how the API actually functions in practice. This, alongside additional deterministic context, will help agents understand your systems in a human-like context without having to have a human on the other side of the request.

The goal: Provide documentation not just of individual endpoints but of the collective flow between them, allowing agents to understand your service properly.”

https://nordicapis.com/10-factors-for-checking-your-apis-ai-readiness/

#API #APIs #APIDocumentation #AI #AIAgents #TechnicalWriting #SoftwareDocumentation #APIDesign

Companies Are Making Claude and Codex Talk Like Cavemen to Stop AI’s Soaring Costs: https://www.404media.co/companies-are-making-claude-and-codex-talk-like-cavemen-to-stop-ais-soaring-costs/

In other words, this is when even mid-level managers start to understand why AI is nearly always not good.

#AI #ArtificialIntelligence #TechComm #TechnicalCommunication #TechnicalWriting

Companies Are Making Claude and Codex Talk Like Cavemen to Stop AI’s Soaring Costs: https://www.404media.co/companies-are-making-claude-and-codex-talk-like-cavemen-to-stop-ais-soaring-costs/

In other words, this is when even mid-level managers start to understand why AI is nearly always not good.

#AI #ArtificialIntelligence #TechComm #TechnicalCommunication #TechnicalWriting

Companies Are Making Claude and Codex Talk Like Cavemen to Stop AI’s Soaring Costs: https://www.404media.co/companies-are-making-claude-and-codex-talk-like-cavemen-to-stop-ais-soaring-costs/

In other words, this is when even mid-level managers start to understand why AI is nearly always not good.

#AI #ArtificialIntelligence #TechComm #TechnicalCommunication #TechnicalWriting

Companies Are Making Claude and Codex Talk Like Cavemen to Stop AI’s Soaring Costs: https://www.404media.co/companies-are-making-claude-and-codex-talk-like-cavemen-to-stop-ais-soaring-costs/

In other words, this is when even mid-level managers start to understand why AI is nearly always not good.

#AI #ArtificialIntelligence #TechComm #TechnicalCommunication #TechnicalWriting

Companies Are Making Claude and Codex Talk Like Cavemen to Stop AI’s Soaring Costs: https://www.404media.co/companies-are-making-claude-and-codex-talk-like-cavemen-to-stop-ais-soaring-costs/

In other words, this is when even mid-level managers start to understand why AI is nearly always not good.

#AI #ArtificialIntelligence #TechComm #TechnicalCommunication #TechnicalWriting

"Now let me touch on an undiscussed aspect of skills I find interesting: skills enforce process. When I run my release documentation skill, I perform the same sequence of steps. As such, skills enforce a consistent process.

Some of the steps incorporate healthy habits into docs. For example, in my robust release docs skills, the following steps are followed:

- Analysis of source code comment tags (and any fixes)
- Analysis of logs run after the reference docs build to identify elements missing documentation.
- Analysis as to whether any changes/updates constitute breaking changes
Analysis of documentation corpus to identify needed changes across docs (and any fixes)

If I were doing these steps on my own, I might cut corners with some releases. For example, I probably wouldn’t have time to analyze the log reports or to scan all other documentation for needed updates. The skill helps me do these steps seamlessly.

Additionally, if you define a specific template for publishing, that template gets applied each time you run the skill, which also leads to more consistency."

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #GenerativeAI #LLMs #Chatbots #Skills #Claude #Gemini #TechnicalWriting #SoftwareDocumentation

"Now let me touch on an undiscussed aspect of skills I find interesting: skills enforce process. When I run my release documentation skill, I perform the same sequence of steps. As such, skills enforce a consistent process.

Some of the steps incorporate healthy habits into docs. For example, in my robust release docs skills, the following steps are followed:

- Analysis of source code comment tags (and any fixes)
- Analysis of logs run after the reference docs build to identify elements missing documentation.
- Analysis as to whether any changes/updates constitute breaking changes
Analysis of documentation corpus to identify needed changes across docs (and any fixes)

If I were doing these steps on my own, I might cut corners with some releases. For example, I probably wouldn’t have time to analyze the log reports or to scan all other documentation for needed updates. The skill helps me do these steps seamlessly.

Additionally, if you define a specific template for publishing, that template gets applied each time you run the skill, which also leads to more consistency."

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #GenerativeAI #LLMs #Chatbots #Skills #Claude #Gemini #TechnicalWriting #SoftwareDocumentation

"Now let me touch on an undiscussed aspect of skills I find interesting: skills enforce process. When I run my release documentation skill, I perform the same sequence of steps. As such, skills enforce a consistent process.

Some of the steps incorporate healthy habits into docs. For example, in my robust release docs skills, the following steps are followed:

- Analysis of source code comment tags (and any fixes)
- Analysis of logs run after the reference docs build to identify elements missing documentation.
- Analysis as to whether any changes/updates constitute breaking changes
Analysis of documentation corpus to identify needed changes across docs (and any fixes)

If I were doing these steps on my own, I might cut corners with some releases. For example, I probably wouldn’t have time to analyze the log reports or to scan all other documentation for needed updates. The skill helps me do these steps seamlessly.

Additionally, if you define a specific template for publishing, that template gets applied each time you run the skill, which also leads to more consistency."

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #GenerativeAI #LLMs #Chatbots #Skills #Claude #Gemini #TechnicalWriting #SoftwareDocumentation

"Now let me touch on an undiscussed aspect of skills I find interesting: skills enforce process. When I run my release documentation skill, I perform the same sequence of steps. As such, skills enforce a consistent process.

Some of the steps incorporate healthy habits into docs. For example, in my robust release docs skills, the following steps are followed:

- Analysis of source code comment tags (and any fixes)
- Analysis of logs run after the reference docs build to identify elements missing documentation.
- Analysis as to whether any changes/updates constitute breaking changes
Analysis of documentation corpus to identify needed changes across docs (and any fixes)

If I were doing these steps on my own, I might cut corners with some releases. For example, I probably wouldn’t have time to analyze the log reports or to scan all other documentation for needed updates. The skill helps me do these steps seamlessly.

Additionally, if you define a specific template for publishing, that template gets applied each time you run the skill, which also leads to more consistency."

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #GenerativeAI #LLMs #Chatbots #Skills #Claude #Gemini #TechnicalWriting #SoftwareDocumentation

"Now let me touch on an undiscussed aspect of skills I find interesting: skills enforce process. When I run my release documentation skill, I perform the same sequence of steps. As such, skills enforce a consistent process.

Some of the steps incorporate healthy habits into docs. For example, in my robust release docs skills, the following steps are followed:

- Analysis of source code comment tags (and any fixes)
- Analysis of logs run after the reference docs build to identify elements missing documentation.
- Analysis as to whether any changes/updates constitute breaking changes
Analysis of documentation corpus to identify needed changes across docs (and any fixes)

If I were doing these steps on my own, I might cut corners with some releases. For example, I probably wouldn’t have time to analyze the log reports or to scan all other documentation for needed updates. The skill helps me do these steps seamlessly.

Additionally, if you define a specific template for publishing, that template gets applied each time you run the skill, which also leads to more consistency."

https://idratherbewriting.com/blog/all-about-skills-intro

#AI #GenerativeAI #LLMs #Chatbots #Skills #Claude #Gemini #TechnicalWriting #SoftwareDocumentation

I tested Sonnet 5 in both low effort and high effort modes for my documentation tasks. While Sonnet 5 in high effort mode delivers some results comparable to Opus, it consumes significantly more tokens than Opus 4.8 in low effort mode. Opus 4.8 low effort remains the more efficient choice for my workflow.

#AI #TechnicalWriting #Efficiency

I tested Sonnet 5 in both low effort and high effort modes for my documentation tasks. While Sonnet 5 in high effort mode delivers some results comparable to Opus, it consumes significantly more tokens than Opus 4.8 in low effort mode. Opus 4.8 low effort remains the more efficient choice for my workflow.

#AI #TechnicalWriting #Efficiency

I tested Sonnet 5 in both low effort and high effort modes for my documentation tasks. While Sonnet 5 in high effort mode delivers some results comparable to Opus, it consumes significantly more tokens than Opus 4.8 in low effort mode. Opus 4.8 low effort remains the more efficient choice for my workflow.

#AI #TechnicalWriting #Efficiency

"Plain English is the discipline of choosing the simplest word that carries the full meaning. It doesn't reduce accuracy. It reduces the cognitive load required to extract accuracy from the text."

https://www.linkedin.com/pulse/plain-english-being-understood-across-time-zones-carrie-warner-wsc1e/

#Writing #Language #TechnicalCommunication #Technicalwriting

"Plain English is the discipline of choosing the simplest word that carries the full meaning. It doesn't reduce accuracy. It reduces the cognitive load required to extract accuracy from the text."

https://www.linkedin.com/pulse/plain-english-being-understood-across-time-zones-carrie-warner-wsc1e/

#Writing #Language #TechnicalCommunication #Technicalwriting

"Plain English is the discipline of choosing the simplest word that carries the full meaning. It doesn't reduce accuracy. It reduces the cognitive load required to extract accuracy from the text."

https://www.linkedin.com/pulse/plain-english-being-understood-across-time-zones-carrie-warner-wsc1e/

#Writing #Language #TechnicalCommunication #Technicalwriting

"Plain English is the discipline of choosing the simplest word that carries the full meaning. It doesn't reduce accuracy. It reduces the cognitive load required to extract accuracy from the text."

https://www.linkedin.com/pulse/plain-english-being-understood-across-time-zones-carrie-warner-wsc1e/

#Writing #Language #TechnicalCommunication #Technicalwriting

"Plain English is the discipline of choosing the simplest word that carries the full meaning. It doesn't reduce accuracy. It reduces the cognitive load required to extract accuracy from the text."

https://www.linkedin.com/pulse/plain-english-being-understood-across-time-zones-carrie-warner-wsc1e/

#Writing #Language #TechnicalCommunication #Technicalwriting

Even with AI providing significant assistance in technical writing, it remains important to aim for content that is as low maintenance as possible.

#TechnicalWriting #AI #ContentStrategy

Hey people in the #UnitedStates, is it worth applying for jobs on #LinkedIn? Specifically in #TechnicalWriting, #Proofreading, and Document #formatting?

I have not heard good things.

As a former tech journalist, I wholeheartedly agree with this!!

"A tech writer is that person who, like a seasoned reporter, chases the product news and presents it, making sure that they’ve collected the strongest evidence. It’s a matter of persistence. Like a particularly learned bulldog, the human writer won’t let go of the news: it’s theirs to bring past the finish line, which means going live, even if the outcome is rough around the edges. DevRels, once shunned by tech writers, are being vindicated in that their humanity is the only thing that can stand out in seas of slop.

For years, we have complained about being treated like formatting factories or syntax janitors. Now that AI is taking those tasks off our plates, and with them a certain comfort zone, we seem afraid to admit that our work is about chasing truth and providing fellow humans with direction. We are in the business of empowering people to build incredible stuff through AI, not that of sticking sentences together in files and chunking content using some dialect of XML. We can no longer hide behind chores: it’s time to guide."

https://passo.uno/tech-writing-role-split/

#AI #GenerativeAI #TechnicalWriting #AIAgents #SoftwareDocumentation #TechnicalCommunication #Docs #LLMs

As a former tech journalist, I wholeheartedly agree with this!!

"A tech writer is that person who, like a seasoned reporter, chases the product news and presents it, making sure that they’ve collected the strongest evidence. It’s a matter of persistence. Like a particularly learned bulldog, the human writer won’t let go of the news: it’s theirs to bring past the finish line, which means going live, even if the outcome is rough around the edges. DevRels, once shunned by tech writers, are being vindicated in that their humanity is the only thing that can stand out in seas of slop.

For years, we have complained about being treated like formatting factories or syntax janitors. Now that AI is taking those tasks off our plates, and with them a certain comfort zone, we seem afraid to admit that our work is about chasing truth and providing fellow humans with direction. We are in the business of empowering people to build incredible stuff through AI, not that of sticking sentences together in files and chunking content using some dialect of XML. We can no longer hide behind chores: it’s time to guide."

https://passo.uno/tech-writing-role-split/

#AI #GenerativeAI #TechnicalWriting #AIAgents #SoftwareDocumentation #TechnicalCommunication #Docs #LLMs

As a former tech journalist, I wholeheartedly agree with this!!

"A tech writer is that person who, like a seasoned reporter, chases the product news and presents it, making sure that they’ve collected the strongest evidence. It’s a matter of persistence. Like a particularly learned bulldog, the human writer won’t let go of the news: it’s theirs to bring past the finish line, which means going live, even if the outcome is rough around the edges. DevRels, once shunned by tech writers, are being vindicated in that their humanity is the only thing that can stand out in seas of slop.

For years, we have complained about being treated like formatting factories or syntax janitors. Now that AI is taking those tasks off our plates, and with them a certain comfort zone, we seem afraid to admit that our work is about chasing truth and providing fellow humans with direction. We are in the business of empowering people to build incredible stuff through AI, not that of sticking sentences together in files and chunking content using some dialect of XML. We can no longer hide behind chores: it’s time to guide."

https://passo.uno/tech-writing-role-split/

#AI #GenerativeAI #TechnicalWriting #AIAgents #SoftwareDocumentation #TechnicalCommunication #Docs #LLMs

As a former tech journalist, I wholeheartedly agree with this!!

"A tech writer is that person who, like a seasoned reporter, chases the product news and presents it, making sure that they’ve collected the strongest evidence. It’s a matter of persistence. Like a particularly learned bulldog, the human writer won’t let go of the news: it’s theirs to bring past the finish line, which means going live, even if the outcome is rough around the edges. DevRels, once shunned by tech writers, are being vindicated in that their humanity is the only thing that can stand out in seas of slop.

For years, we have complained about being treated like formatting factories or syntax janitors. Now that AI is taking those tasks off our plates, and with them a certain comfort zone, we seem afraid to admit that our work is about chasing truth and providing fellow humans with direction. We are in the business of empowering people to build incredible stuff through AI, not that of sticking sentences together in files and chunking content using some dialect of XML. We can no longer hide behind chores: it’s time to guide."

https://passo.uno/tech-writing-role-split/

#AI #GenerativeAI #TechnicalWriting #AIAgents #SoftwareDocumentation #TechnicalCommunication #Docs #LLMs

As a former tech journalist, I wholeheartedly agree with this!!

"A tech writer is that person who, like a seasoned reporter, chases the product news and presents it, making sure that they’ve collected the strongest evidence. It’s a matter of persistence. Like a particularly learned bulldog, the human writer won’t let go of the news: it’s theirs to bring past the finish line, which means going live, even if the outcome is rough around the edges. DevRels, once shunned by tech writers, are being vindicated in that their humanity is the only thing that can stand out in seas of slop.

For years, we have complained about being treated like formatting factories or syntax janitors. Now that AI is taking those tasks off our plates, and with them a certain comfort zone, we seem afraid to admit that our work is about chasing truth and providing fellow humans with direction. We are in the business of empowering people to build incredible stuff through AI, not that of sticking sentences together in files and chunking content using some dialect of XML. We can no longer hide behind chores: it’s time to guide."

https://passo.uno/tech-writing-role-split/

#AI #GenerativeAI #TechnicalWriting #AIAgents #SoftwareDocumentation #TechnicalCommunication #Docs #LLMs

I finally made the switch to Opus 4.8 with minimal effort. Previously, using Opus 4.7 for technical writing tasks consumed tokens at an unsustainable rate. Now, with the same workflows and likely some fine-tuning by Anthropic, I managed a heavy load of documentation requests this week. Token consumption is now much more manageable.

#AI #TechnicalWriting #Efficiency

I finally made the switch to Opus 4.8 with minimal effort. Previously, using Opus 4.7 for technical writing tasks consumed tokens at an unsustainable rate. Now, with the same workflows and likely some fine-tuning by Anthropic, I managed a heavy load of documentation requests this week. Token consumption is now much more manageable.

#AI #TechnicalWriting #Efficiency

I finally made the switch to Opus 4.8 with minimal effort. Previously, using Opus 4.7 for technical writing tasks consumed tokens at an unsustainable rate. Now, with the same workflows and likely some fine-tuning by Anthropic, I managed a heavy load of documentation requests this week. Token consumption is now much more manageable.

#AI #TechnicalWriting #Efficiency

I finally made the switch to Opus 4.8 with minimal effort. Previously, using Opus 4.7 for technical writing tasks consumed tokens at an unsustainable rate. Now, with the same workflows and likely some fine-tuning by Anthropic, I managed a heavy load of documentation requests this week. Token consumption is now much more manageable.

#AI #TechnicalWriting #Efficiency

I finally made the switch to Opus 4.8 with minimal effort. Previously, using Opus 4.7 for technical writing tasks consumed tokens at an unsustainable rate. Now, with the same workflows and likely some fine-tuning by Anthropic, I managed a heavy load of documentation requests this week. Token consumption is now much more manageable.

#AI #TechnicalWriting #Efficiency

"An engineer named Siddhant Khare wrote recently about what he called “AI fatigue” — the exhaustion that comes not from creating but from reviewing. Before AI, his day had a rhythm: think about a problem, write code, test it, ship it. After AI, his day became a loop of prompting, waiting, reading output, evaluating output, deciding if the output was correct, deciding if it was safe, fixing the parts that weren’t, and re-prompting. He described it as becoming a quality inspector on a conveyor belt that never stops. The work was faster but emptier. The flow states that used to sustain him — the deep, energizing focus of building something yourself — had been replaced by the shallow, draining focus of judging something you didn’t build.

Not every writer experiences this the same way. For some, the shift is actually liberating. If your day job involves writing yet another SDK migration guide or documenting the fine-grained differences between configuration parameters across product tiers — content you won’t remember in a month — there’s no loss of creative joy when the machine drafts it for you. You become the editor, not the author, and you save your real creative energy for work that matters to you personally. The fatigue isn’t from reviewing; it’s from pretending that all documentation deserves the same emotional investment. Some of it is toil, and outsourcing toil is fine.

But here’s the tension: if you stop caring about the work the machine produces, who maintains the quality? This is where the concept of ownership becomes critical. The tech writers who thrive in this landscape aren’t the ones who wait for engineers to hand them drafts to edit. They’re the ones who own the reference documentation, who run diffs against every API release, who update architectural diagrams, who maintain a single source of truth..."

https://idratherbewriting.com/blog/judging-beautiful-docs-ai-fatigue-podcast

#TechnicalWriting #AI #GenerativeAI #SoftwareDocumentation #TechnicalCommunication #Docs #Programming #SoftwareDevelopment

"An engineer named Siddhant Khare wrote recently about what he called “AI fatigue” — the exhaustion that comes not from creating but from reviewing. Before AI, his day had a rhythm: think about a problem, write code, test it, ship it. After AI, his day became a loop of prompting, waiting, reading output, evaluating output, deciding if the output was correct, deciding if it was safe, fixing the parts that weren’t, and re-prompting. He described it as becoming a quality inspector on a conveyor belt that never stops. The work was faster but emptier. The flow states that used to sustain him — the deep, energizing focus of building something yourself — had been replaced by the shallow, draining focus of judging something you didn’t build.

Not every writer experiences this the same way. For some, the shift is actually liberating. If your day job involves writing yet another SDK migration guide or documenting the fine-grained differences between configuration parameters across product tiers — content you won’t remember in a month — there’s no loss of creative joy when the machine drafts it for you. You become the editor, not the author, and you save your real creative energy for work that matters to you personally. The fatigue isn’t from reviewing; it’s from pretending that all documentation deserves the same emotional investment. Some of it is toil, and outsourcing toil is fine.

But here’s the tension: if you stop caring about the work the machine produces, who maintains the quality? This is where the concept of ownership becomes critical. The tech writers who thrive in this landscape aren’t the ones who wait for engineers to hand them drafts to edit. They’re the ones who own the reference documentation, who run diffs against every API release, who update architectural diagrams, who maintain a single source of truth..."

https://idratherbewriting.com/blog/judging-beautiful-docs-ai-fatigue-podcast

#TechnicalWriting #AI #GenerativeAI #SoftwareDocumentation #TechnicalCommunication #Docs #Programming #SoftwareDevelopment

"An engineer named Siddhant Khare wrote recently about what he called “AI fatigue” — the exhaustion that comes not from creating but from reviewing. Before AI, his day had a rhythm: think about a problem, write code, test it, ship it. After AI, his day became a loop of prompting, waiting, reading output, evaluating output, deciding if the output was correct, deciding if it was safe, fixing the parts that weren’t, and re-prompting. He described it as becoming a quality inspector on a conveyor belt that never stops. The work was faster but emptier. The flow states that used to sustain him — the deep, energizing focus of building something yourself — had been replaced by the shallow, draining focus of judging something you didn’t build.

Not every writer experiences this the same way. For some, the shift is actually liberating. If your day job involves writing yet another SDK migration guide or documenting the fine-grained differences between configuration parameters across product tiers — content you won’t remember in a month — there’s no loss of creative joy when the machine drafts it for you. You become the editor, not the author, and you save your real creative energy for work that matters to you personally. The fatigue isn’t from reviewing; it’s from pretending that all documentation deserves the same emotional investment. Some of it is toil, and outsourcing toil is fine.

But here’s the tension: if you stop caring about the work the machine produces, who maintains the quality? This is where the concept of ownership becomes critical. The tech writers who thrive in this landscape aren’t the ones who wait for engineers to hand them drafts to edit. They’re the ones who own the reference documentation, who run diffs against every API release, who update architectural diagrams, who maintain a single source of truth..."

https://idratherbewriting.com/blog/judging-beautiful-docs-ai-fatigue-podcast

#TechnicalWriting #AI #GenerativeAI #SoftwareDocumentation #TechnicalCommunication #Docs #Programming #SoftwareDevelopment

"An engineer named Siddhant Khare wrote recently about what he called “AI fatigue” — the exhaustion that comes not from creating but from reviewing. Before AI, his day had a rhythm: think about a problem, write code, test it, ship it. After AI, his day became a loop of prompting, waiting, reading output, evaluating output, deciding if the output was correct, deciding if it was safe, fixing the parts that weren’t, and re-prompting. He described it as becoming a quality inspector on a conveyor belt that never stops. The work was faster but emptier. The flow states that used to sustain him — the deep, energizing focus of building something yourself — had been replaced by the shallow, draining focus of judging something you didn’t build.

Not every writer experiences this the same way. For some, the shift is actually liberating. If your day job involves writing yet another SDK migration guide or documenting the fine-grained differences between configuration parameters across product tiers — content you won’t remember in a month — there’s no loss of creative joy when the machine drafts it for you. You become the editor, not the author, and you save your real creative energy for work that matters to you personally. The fatigue isn’t from reviewing; it’s from pretending that all documentation deserves the same emotional investment. Some of it is toil, and outsourcing toil is fine.

But here’s the tension: if you stop caring about the work the machine produces, who maintains the quality? This is where the concept of ownership becomes critical. The tech writers who thrive in this landscape aren’t the ones who wait for engineers to hand them drafts to edit. They’re the ones who own the reference documentation, who run diffs against every API release, who update architectural diagrams, who maintain a single source of truth..."

https://idratherbewriting.com/blog/judging-beautiful-docs-ai-fatigue-podcast

#TechnicalWriting #AI #GenerativeAI #SoftwareDocumentation #TechnicalCommunication #Docs #Programming #SoftwareDevelopment

"An engineer named Siddhant Khare wrote recently about what he called “AI fatigue” — the exhaustion that comes not from creating but from reviewing. Before AI, his day had a rhythm: think about a problem, write code, test it, ship it. After AI, his day became a loop of prompting, waiting, reading output, evaluating output, deciding if the output was correct, deciding if it was safe, fixing the parts that weren’t, and re-prompting. He described it as becoming a quality inspector on a conveyor belt that never stops. The work was faster but emptier. The flow states that used to sustain him — the deep, energizing focus of building something yourself — had been replaced by the shallow, draining focus of judging something you didn’t build.

Not every writer experiences this the same way. For some, the shift is actually liberating. If your day job involves writing yet another SDK migration guide or documenting the fine-grained differences between configuration parameters across product tiers — content you won’t remember in a month — there’s no loss of creative joy when the machine drafts it for you. You become the editor, not the author, and you save your real creative energy for work that matters to you personally. The fatigue isn’t from reviewing; it’s from pretending that all documentation deserves the same emotional investment. Some of it is toil, and outsourcing toil is fine.

But here’s the tension: if you stop caring about the work the machine produces, who maintains the quality? This is where the concept of ownership becomes critical. The tech writers who thrive in this landscape aren’t the ones who wait for engineers to hand them drafts to edit. They’re the ones who own the reference documentation, who run diffs against every API release, who update architectural diagrams, who maintain a single source of truth..."

https://idratherbewriting.com/blog/judging-beautiful-docs-ai-fatigue-podcast

#TechnicalWriting #AI #GenerativeAI #SoftwareDocumentation #TechnicalCommunication #Docs #Programming #SoftwareDevelopment

First-time speakers are warmly encouraged, especially if you’ve done useful docs work but haven’t spoken about it publicly before.

Submit a proposal even if you’re still shaping the talk. We’d be happy to see the idea early.

#IndiaFOSS #WriteTheDocs #TechnicalWriting

First-time speakers are warmly encouraged, especially if you’ve done useful docs work but haven’t spoken about it publicly before.

Submit a proposal even if you’re still shaping the talk. We’d be happy to see the idea early.

#IndiaFOSS #WriteTheDocs #TechnicalWriting

First-time speakers are warmly encouraged, especially if you’ve done useful docs work but haven’t spoken about it publicly before.

Submit a proposal even if you’re still shaping the talk. We’d be happy to see the idea early.

#IndiaFOSS #WriteTheDocs #TechnicalWriting

First-time speakers are warmly encouraged, especially if you’ve done useful docs work but haven’t spoken about it publicly before.

Submit a proposal even if you’re still shaping the talk. We’d be happy to see the idea early.

#IndiaFOSS #WriteTheDocs #TechnicalWriting

First-time speakers are warmly encouraged, especially if you’ve done useful docs work but haven’t spoken about it publicly before.

Submit a proposal even if you’re still shaping the talk. We’d be happy to see the idea early.

#IndiaFOSS #WriteTheDocs #TechnicalWriting

I'm streaming KDE docs:

• right now!
• on https://live.rabbitictranslator.com
• on https://twitch.tv/herzenschein

I'm streaming to both Owncast and Twitch right now.

My shoulder and back are not great today, but I should be able to stream for one hour or two.

Be sure to join and ask any questions related to KDE and I'll try my best to answer them.

Every single stream I do is an Ask Me Anything KDE Edition ™️

#KDE #Linux #Documentation #TechnicalWriting #FurryStreamer #FurryVTuber #VTuber #Owncast #Twitch

I'm streaming KDE docs:

• right now!
• on https://live.rabbitictranslator.com
• on https://twitch.tv/herzenschein

I'm streaming to both Owncast and Twitch right now.

My shoulder and back are not great today, but I should be able to stream for one hour or two.

Be sure to join and ask any questions related to KDE and I'll try my best to answer them.

Every single stream I do is an Ask Me Anything KDE Edition ™️

#KDE #Linux #Documentation #TechnicalWriting #FurryStreamer #FurryVTuber #VTuber #Owncast #Twitch

I'm streaming KDE docs:

• right now!
• on https://live.rabbitictranslator.com
• on https://twitch.tv/herzenschein

I'm streaming to both Owncast and Twitch right now.

My shoulder and back are not great today, but I should be able to stream for one hour or two.

Be sure to join and ask any questions related to KDE and I'll try my best to answer them.

Every single stream I do is an Ask Me Anything KDE Edition ™️

#KDE #Linux #Documentation #TechnicalWriting #FurryStreamer #FurryVTuber #VTuber #Owncast #Twitch

I'm streaming KDE docs:

• right now!
• on https://live.rabbitictranslator.com
• on https://twitch.tv/herzenschein

I'm streaming to both Owncast and Twitch right now.

My shoulder and back are not great today, but I should be able to stream for one hour or two.

Be sure to join and ask any questions related to KDE and I'll try my best to answer them.

Every single stream I do is an Ask Me Anything KDE Edition ™️

#KDE #Linux #Documentation #TechnicalWriting #FurryStreamer #FurryVTuber #VTuber #Owncast #Twitch

"If you are thinking about using an AI agent for documentation, here is what I think matters most.

Teach the agent, do not just instruct it. A prompt that says "write documentation for this feature" produces generic content. A skill that defines your voice, your formatting rules, your page structure, and your verification checklist produces documentation that sounds like your team wrote it. The upfront investment in the skill pays off on every subsequent page.

Make screenshots reproducible. Manual screenshots are the first thing that goes stale. A declarative manifest that can regenerate every screenshot in one command is worth the engineering effort. It changes screenshots from a one-time cost to a maintained artifact.

Phase your work. Even if you are using an agent, "write all the docs" is not a plan. Break it into phases with clear scope and clear deliverables. This gives you stopping points, review points, and the ability to course-correct.

Expect things to break. OCR will misread text. The UI will change mid-sprint. Preview URLs will go stale. The difference between a frustrating experience and a productive one is whether you encode the fix into a skill so it never happens again.

Review everything. The agent does not replace your judgment. It replaces the mechanical work. You still need to read every page, check every screenshot, and verify that the documentation matches what the user actually sees. The agent writes the first draft. You make it right."

https://dev.to/debs_obrien/how-i-documented-an-entire-product-in-4-days-with-an-ai-agent-3338

#TechnicalWriting #SoftwareDocumentation #AI #GenerativeAI #AIAgents #AgenticAI #LLMs

"If you are thinking about using an AI agent for documentation, here is what I think matters most.

Teach the agent, do not just instruct it. A prompt that says "write documentation for this feature" produces generic content. A skill that defines your voice, your formatting rules, your page structure, and your verification checklist produces documentation that sounds like your team wrote it. The upfront investment in the skill pays off on every subsequent page.

Make screenshots reproducible. Manual screenshots are the first thing that goes stale. A declarative manifest that can regenerate every screenshot in one command is worth the engineering effort. It changes screenshots from a one-time cost to a maintained artifact.

Phase your work. Even if you are using an agent, "write all the docs" is not a plan. Break it into phases with clear scope and clear deliverables. This gives you stopping points, review points, and the ability to course-correct.

Expect things to break. OCR will misread text. The UI will change mid-sprint. Preview URLs will go stale. The difference between a frustrating experience and a productive one is whether you encode the fix into a skill so it never happens again.

Review everything. The agent does not replace your judgment. It replaces the mechanical work. You still need to read every page, check every screenshot, and verify that the documentation matches what the user actually sees. The agent writes the first draft. You make it right."

https://dev.to/debs_obrien/how-i-documented-an-entire-product-in-4-days-with-an-ai-agent-3338

#TechnicalWriting #SoftwareDocumentation #AI #GenerativeAI #AIAgents #AgenticAI #LLMs

"If you are thinking about using an AI agent for documentation, here is what I think matters most.

Teach the agent, do not just instruct it. A prompt that says "write documentation for this feature" produces generic content. A skill that defines your voice, your formatting rules, your page structure, and your verification checklist produces documentation that sounds like your team wrote it. The upfront investment in the skill pays off on every subsequent page.

Make screenshots reproducible. Manual screenshots are the first thing that goes stale. A declarative manifest that can regenerate every screenshot in one command is worth the engineering effort. It changes screenshots from a one-time cost to a maintained artifact.

Phase your work. Even if you are using an agent, "write all the docs" is not a plan. Break it into phases with clear scope and clear deliverables. This gives you stopping points, review points, and the ability to course-correct.

Expect things to break. OCR will misread text. The UI will change mid-sprint. Preview URLs will go stale. The difference between a frustrating experience and a productive one is whether you encode the fix into a skill so it never happens again.

Review everything. The agent does not replace your judgment. It replaces the mechanical work. You still need to read every page, check every screenshot, and verify that the documentation matches what the user actually sees. The agent writes the first draft. You make it right."

https://dev.to/debs_obrien/how-i-documented-an-entire-product-in-4-days-with-an-ai-agent-3338

#TechnicalWriting #SoftwareDocumentation #AI #GenerativeAI #AIAgents #AgenticAI #LLMs

"If you are thinking about using an AI agent for documentation, here is what I think matters most.

Teach the agent, do not just instruct it. A prompt that says "write documentation for this feature" produces generic content. A skill that defines your voice, your formatting rules, your page structure, and your verification checklist produces documentation that sounds like your team wrote it. The upfront investment in the skill pays off on every subsequent page.

Make screenshots reproducible. Manual screenshots are the first thing that goes stale. A declarative manifest that can regenerate every screenshot in one command is worth the engineering effort. It changes screenshots from a one-time cost to a maintained artifact.

Phase your work. Even if you are using an agent, "write all the docs" is not a plan. Break it into phases with clear scope and clear deliverables. This gives you stopping points, review points, and the ability to course-correct.

Expect things to break. OCR will misread text. The UI will change mid-sprint. Preview URLs will go stale. The difference between a frustrating experience and a productive one is whether you encode the fix into a skill so it never happens again.

Review everything. The agent does not replace your judgment. It replaces the mechanical work. You still need to read every page, check every screenshot, and verify that the documentation matches what the user actually sees. The agent writes the first draft. You make it right."

https://dev.to/debs_obrien/how-i-documented-an-entire-product-in-4-days-with-an-ai-agent-3338

#TechnicalWriting #SoftwareDocumentation #AI #GenerativeAI #AIAgents #AgenticAI #LLMs

"If you are thinking about using an AI agent for documentation, here is what I think matters most.

Teach the agent, do not just instruct it. A prompt that says "write documentation for this feature" produces generic content. A skill that defines your voice, your formatting rules, your page structure, and your verification checklist produces documentation that sounds like your team wrote it. The upfront investment in the skill pays off on every subsequent page.

Make screenshots reproducible. Manual screenshots are the first thing that goes stale. A declarative manifest that can regenerate every screenshot in one command is worth the engineering effort. It changes screenshots from a one-time cost to a maintained artifact.

Phase your work. Even if you are using an agent, "write all the docs" is not a plan. Break it into phases with clear scope and clear deliverables. This gives you stopping points, review points, and the ability to course-correct.

Expect things to break. OCR will misread text. The UI will change mid-sprint. Preview URLs will go stale. The difference between a frustrating experience and a productive one is whether you encode the fix into a skill so it never happens again.

Review everything. The agent does not replace your judgment. It replaces the mechanical work. You still need to read every page, check every screenshot, and verify that the documentation matches what the user actually sees. The agent writes the first draft. You make it right."

https://dev.to/debs_obrien/how-i-documented-an-entire-product-in-4-days-with-an-ai-agent-3338

#TechnicalWriting #SoftwareDocumentation #AI #GenerativeAI #AIAgents #AgenticAI #LLMs

"The future of enterprise technical documentation will not belong to organizations that merely generate more content with AI. It will belong to organizations that build semantically governed, operationally validated, and explainable knowledge ecosystems around AI generation.

Large language models are remarkable language-generation systems, but they remain fundamentally probabilistic, and no amount of vector-based probabilistic augmentation, recursive prompt gymnastics, or trillions of additional parameters magically transforms probabilistic token prediction into deterministic operational intelligence — regardless of what the AI snake-oil salesmen on LinkedIn insist between inspirational rocket-ship emojis. LLMs predict statistically likely outputs. They do not inherently understand operational correctness, governance policy, procedural safety, rollback integrity, regulatory compliance, or whether the “helpful” configuration change they just suggested is going to quietly detonate a production Kubernetes cluster at 2:13 a.m. while everyone is asleep and the on-call engineer is reconsidering their career choices.

That is not a moral failure of AI. It is simply the architectural reality of probabilistic systems pretending to perform deterministic operational reasoning often enough to make people dangerously optimistic.

This is precisely why deterministic models and governance matter.

Structured content, semantic markup, metadata governance, provenance tracking, DOM Graph RAG, iiRDS frameworks, knowledge graphs, RDF and OWL ontologies, context graphs, deterministic inference engines, orchestration platforms, Docs-as-Tests automation, and runtime observability together create something fundamentally different from prompt engineering. They create governed operational ecosystems capable of supporting trustworthy enterprise AI at scale."

https://medium.com/@nc_mike/deterministic-and-agentic-ai-architectures-for-technical-documentation-3fb2956a1334

#AI #GenerativeAI #DocsAsTests #LLMs #AgenticAI #DITAXML #AIAgents #TechnicalWriting #SoftwareDocumentation