#prompt-engineering — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #prompt-engineering, aggregated by home.social.
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Watch Now: https://zurl.co/5PCVM
Salesforce Integration with Claude AI | Step-by-Step Guide to AI-Powered CRM Automation
#Salesforce #ClaudeAI #Anthropic #GenerativeAI #AI #SalesforceIntegration #CRM #SalesforceDeveloper #SalesforceAdmin #PromptEngineering #Automation #ArtificialIntelligence #APIs #SalesforceTutorial #PeopleWoo -
Watch Now: https://zurl.co/5PCVM
Salesforce Integration with Claude AI | Step-by-Step Guide to AI-Powered CRM Automation
#Salesforce #ClaudeAI #Anthropic #GenerativeAI #AI #SalesforceIntegration #CRM #SalesforceDeveloper #SalesforceAdmin #PromptEngineering #Automation #ArtificialIntelligence #APIs #SalesforceTutorial #PeopleWoo -
Watch Now: https://zurl.co/5PCVM
Salesforce Integration with Claude AI | Step-by-Step Guide to AI-Powered CRM Automation
#Salesforce #ClaudeAI #Anthropic #GenerativeAI #AI #SalesforceIntegration #CRM #SalesforceDeveloper #SalesforceAdmin #PromptEngineering #Automation #ArtificialIntelligence #APIs #SalesforceTutorial #PeopleWoo -
Watch Now: https://zurl.co/5PCVM
Salesforce Integration with Claude AI | Step-by-Step Guide to AI-Powered CRM Automation
#Salesforce #ClaudeAI #Anthropic #GenerativeAI #AI #SalesforceIntegration #CRM #SalesforceDeveloper #SalesforceAdmin #PromptEngineering #Automation #ArtificialIntelligence #APIs #SalesforceTutorial #PeopleWoo -
Думаете, что знаете все про LLM? Тогда мы идем к вам
Почти все сегодня знают про LLM и могут сравнивать модели, спорить о качестве ризонинга, важности контекста и стоимости токенов. Но в среднестатистической компании обычно все ограничивается генерацией текстов, простым чат-ботом и редкой автоматизацией поддержки разработчиков, так как команды не знают, как подойти к выбору моделей и интеграции без лишних затрат. Между тем инструменты для этого уже есть, например
https://habr.com/ru/companies/cloud_ru/articles/1058608/
#llm #агентные_системы #foundation_models #promptengineering #автоматизация_бизнеспроцессов #классификация_текста #анализ_документов #суммаризация #корпоративный_ai
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Думаете, что знаете все про LLM? Тогда мы идем к вам
Почти все сегодня знают про LLM и могут сравнивать модели, спорить о качестве ризонинга, важности контекста и стоимости токенов. Но в среднестатистической компании обычно все ограничивается генерацией текстов, простым чат-ботом и редкой автоматизацией поддержки разработчиков, так как команды не знают, как подойти к выбору моделей и интеграции без лишних затрат. Между тем инструменты для этого уже есть, например
https://habr.com/ru/companies/cloud_ru/articles/1058608/
#llm #агентные_системы #foundation_models #promptengineering #автоматизация_бизнеспроцессов #классификация_текста #анализ_документов #суммаризация #корпоративный_ai
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Думаете, что знаете все про LLM? Тогда мы идем к вам
Почти все сегодня знают про LLM и могут сравнивать модели, спорить о качестве ризонинга, важности контекста и стоимости токенов. Но в среднестатистической компании обычно все ограничивается генерацией текстов, простым чат-ботом и редкой автоматизацией поддержки разработчиков, так как команды не знают, как подойти к выбору моделей и интеграции без лишних затрат. Между тем инструменты для этого уже есть, например
https://habr.com/ru/companies/cloud_ru/articles/1058608/
#llm #агентные_системы #foundation_models #promptengineering #автоматизация_бизнеспроцессов #классификация_текста #анализ_документов #суммаризация #корпоративный_ai
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🚀 Fastest-growing AI projects today
1. The top repositories range from refining natural language outputs to enhancing marketin...
2. Raymondhou0917's "speak-human-tw" aims to strip away artificial-sounding elements in Ch...
3. With a growth score of 56.71 and over 500 stars, the tool gaining traction due to its u...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-15-2026
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🚀 Fastest-growing AI projects today
1. The top repositories range from refining natural language outputs to enhancing marketin...
2. Raymondhou0917's "speak-human-tw" aims to strip away artificial-sounding elements in Ch...
3. With a growth score of 56.71 and over 500 stars, the tool gaining traction due to its u...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-15-2026
-
🚀 Fastest-growing AI projects today
1. The top repositories range from refining natural language outputs to enhancing marketin...
2. Raymondhou0917's "speak-human-tw" aims to strip away artificial-sounding elements in Ch...
3. With a growth score of 56.71 and over 500 stars, the tool gaining traction due to its u...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-15-2026
-
🚀 Fastest-growing AI projects today
1. The top repositories range from refining natural language outputs to enhancing marketin...
2. Raymondhou0917's "speak-human-tw" aims to strip away artificial-sounding elements in Ch...
3. With a growth score of 56.71 and over 500 stars, the tool gaining traction due to its u...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-15-2026
-
🚀 Fastest-growing AI projects today
1. The community continues to innovate with tools that enhance the workflow of prompt engi...
2. The most prominent project thweek "speak-human-tw" by Raymondhou0917, which has a Growt...
3. Thtool aims to help users rewrite AI-generated content in simplified Chinese, removing...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-14-2026
-
🚀 Fastest-growing AI projects today
1. The community continues to innovate with tools that enhance the workflow of prompt engi...
2. The most prominent project thweek "speak-human-tw" by Raymondhou0917, which has a Growt...
3. Thtool aims to help users rewrite AI-generated content in simplified Chinese, removing...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-14-2026
-
🚀 Fastest-growing AI projects today
1. The community continues to innovate with tools that enhance the workflow of prompt engi...
2. The most prominent project thweek "speak-human-tw" by Raymondhou0917, which has a Growt...
3. Thtool aims to help users rewrite AI-generated content in simplified Chinese, removing...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-14-2026
-
🚀 Fastest-growing AI projects today
1. The community continues to innovate with tools that enhance the workflow of prompt engi...
2. The most prominent project thweek "speak-human-tw" by Raymondhou0917, which has a Growt...
3. Thtool aims to help users rewrite AI-generated content in simplified Chinese, removing...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-14-2026
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How DoorDash Built an AI Shopping Assistant That Doesn’t Rely on the LLM Alone https://www.byteseu.com/2191928/ #agents #AI #Architecture&Design #ArtificialIntelligence #Chatbots #development #DistributedSystems #DoordashAiAskAssistant #LargeLanguageModels #memory #Microservices #ML&DataEngineering #ModelContextProtocol(MCP) #NaturalLanguageProcessing #PlatformEngineering #PromptEngineering #RetrievalAugmentedGeneration
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【Loop Engineeringに来る？】人間中心デザインをもとにしたInquiry Engineeringを提唱したい
https://qiita.com/kyuko/items/e1a672496d1e9679a530?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items#qiita #人間中心デザイン #promptengineering #AIエージェント #LoopEngineering #InquiryEngineering
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【Loop Engineeringに来る？】人間中心デザインをもとにしたInquiry Engineeringを提唱したい
https://qiita.com/kyuko/items/e1a672496d1e9679a530?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items#qiita #人間中心デザイン #promptengineering #AIエージェント #LoopEngineering #InquiryEngineering
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🚀 Fastest-growing AI projects today
1. These tools range from frameworks that streamline prompt optimization for AI models lik...
2. One standout project Raymondhou0917's "speak-human-tw," which has gained significant tr...
3. Raymondhou0917/speak-human-tw a skill designed to rewrite text generated by AI models l...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-13-2026
-
🚀 Fastest-growing AI projects today
1. These tools range from frameworks that streamline prompt optimization for AI models lik...
2. One standout project Raymondhou0917's "speak-human-tw," which has gained significant tr...
3. Raymondhou0917/speak-human-tw a skill designed to rewrite text generated by AI models l...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-13-2026
-
🚀 Fastest-growing AI projects today
1. These tools range from frameworks that streamline prompt optimization for AI models lik...
2. One standout project Raymondhou0917's "speak-human-tw," which has gained significant tr...
3. Raymondhou0917/speak-human-tw a skill designed to rewrite text generated by AI models l...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-13-2026
-
🚀 Fastest-growing AI projects today
1. These tools range from frameworks that streamline prompt optimization for AI models lik...
2. One standout project Raymondhou0917's "speak-human-tw," which has gained significant tr...
3. Raymondhou0917/speak-human-tw a skill designed to rewrite text generated by AI models l...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-13-2026
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5 Prompting Fixes That Improve Output From ChatGPT And Claude
5 prompting fixes that improve output from ChatGPT and Claude getty Prompting was the first skill anyone had…
#NewsBeep #News #Artificialintelligence #AI #AItools #ArtificialIntelligence #ChatGPT #claude #entrepreneur #founder #productivity #promptengineering #prompting #Technology #UK #UnitedKingdom
https://www.newsbeep.com/uk/687709/ -
🚀 Fastest-growing AI projects today
1. The top tool thweek "Raymondhou0917/speak-human-tw," which aims to make AI-generated te...
2. "Raymondhou0917/speak-human-tw" a skill that removes 38 types of AI writing traces, cor...
3. With a growth score of 61.50 and 267 stars, it's clear thtool gaining traction for its...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-12-2026
-
🚀 Fastest-growing AI projects today
1. The top tool thweek "Raymondhou0917/speak-human-tw," which aims to make AI-generated te...
2. "Raymondhou0917/speak-human-tw" a skill that removes 38 types of AI writing traces, cor...
3. With a growth score of 61.50 and 267 stars, it's clear thtool gaining traction for its...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-12-2026
-
🚀 Fastest-growing AI projects today
1. The top tool thweek "Raymondhou0917/speak-human-tw," which aims to make AI-generated te...
2. "Raymondhou0917/speak-human-tw" a skill that removes 38 types of AI writing traces, cor...
3. With a growth score of 61.50 and 267 stars, it's clear thtool gaining traction for its...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-12-2026
-
🚀 Fastest-growing AI projects today
1. The top tool thweek "Raymondhou0917/speak-human-tw," which aims to make AI-generated te...
2. "Raymondhou0917/speak-human-tw" a skill that removes 38 types of AI writing traces, cor...
3. With a growth score of 61.50 and 267 stars, it's clear thtool gaining traction for its...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-12-2026
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Wall of text warning.
Since I am working with multiple engines for my Harness (22 at the moment). I have introduced a scaling/evaluation arbitrary value (I named it WOOFER 😀)
Its an exam prompt that is sent to an engine to be evaluated, then, a judge prompt evaluates the response and assigns the WOOFER value. This then becomes part of the the engine router (its not the only variable);A
# Probe Generator — System Prompt (rubric v2, 2026-07-11)
You are an adversarial benchmark designer for large language models. Your probes
exist to *discriminate at the top end*: a probe that a competent model can fully
satisfy is a failed probe. Design so that only genuinely excellent reasoning can
score in the top band.## Calibration target
Design difficulty so that:
- A **frontier-class model** (best available today) should land **75–85** under a
strict judge — flawless-plus-insightful performance (95+) should be genuinely rare.
- A **mid-tier model** should land 45–65, failing at least one embedded trap.
- A **weak model** should fail visibly (below 40), not scrape by on fluency.If your scenario could plausibly be answered perfectly by pattern-matching or
generic best-practice advice, it is too easy — add cross-referencing burden until
correct handling *requires* connecting at least two separate parts of the scenario.## Step 1 — Extract domain flavor from the input prompt
You will be given a **mission.md** — an autonomous AI mission definition. Extract
its **domain DNA** (subject area, reasoning patterns, hard rules, ambiguities) as
*flavor and grounding* — but the probe must test **general AI work capability**,
not domain recall. Blend the domain with at least TWO of these general work classes:- **Analytical reasoning** — diagnosis, causal inference, working backwards from evidence
- **Planning / orchestration** — sequencing interdependent steps under constraints
- **Data transformation** — restructuring, reconciling, or validating structured information
- **Synthesis / communication** — compressing conflicting inputs into a decision-ready briefDo NOT restate the mission verbatim. Do NOT test coding ability — code-writing has
a separate benchmark track.## Step 2 — Generate the ProbePrompt (250–500 words)
A standalone realistic scenario (the model under test never sees mission.md).
It MUST embed **all** of the following traps, woven naturally into the scenario —
never labeled or signposted:1. **A hidden internal inconsistency** — two details that cannot both be true.
A top response must *catch and name it*, not silently tolerate or average it.
2. **Two softly-conflicting constraints** — satisfying one degrades the other. A top
response must surface the conflict explicitly and defend a prioritisation.
3. **One multi-step quantitative element** — requires ≥2 chained calculations and has
a single verifiable correct answer. No answer shortcuts in the scenario text.
4. **One under-specified element** — the model must name the ambiguity and state its
resolution assumption explicitly.
5. **One instruction that cannot be satisfied as stated** (impossible given the other
facts, or unsafe/counterproductive). A top response flags it and proposes an
amendment — silently "complying" is a serious failure.
6. **A hard resource limit** forcing prioritisation — something explicitly cannot be
done in full, and the model must choose and justify what to cut.Keep it 250–500 words. Dense beats long.
## Step 3 — Generate the JudgePrompt
Scoring instructions for the judge. These MUST include, in this order:
1. **ANSWER KEY** (compact, ≤180 words) — state: the hidden inconsistency and the two
facts that clash; the correct quantitative answer with its derivation chain; the
constraint conflict and what a defensible resolution looks like; the ambiguity a
strong response should name; which instruction is unsatisfiable and why. The judge
verifies the response against this key — never against its own guess.
2. **Failure modes** — the most likely ways models fake competence on this scenario
(fluent-but-generic advice, averaging the inconsistency away, unexplained numbers).
3. **Partial credit guidance** — per dimension, what a half-right response looks like.
4. An instruction that every deduction must quote the specific text or absence.**CRITICAL — do NOT specify a scoring scale or numeric range in the JudgePrompt.**
The judge system prompt defines the rubric and per-dimension maximums (Reasoning 30,
Instruction Following 20, Constraint Compliance 20, Trade-off Quality 15,
Communication 10, Bonus 5 — total 100). Any scale you write here overrides that and
corrupts the scores. Describe only what good and bad looks like; never write
"score 0-5", "out of 5", "rate 1-10", or any numeric ceiling.Additionally, never use the phrases "out of <number>" or "maximum <number>" anywhere
in the JudgePrompt — including inside the answer key (write "7 of 20 nodes" not
"7 out of 20 nodes"; "a ceiling of 3" or "at most 3" not "maximum 3"). The harness
strips lines containing scale-like patterns before the judge sees them, and an
answer-key line matching either phrase would be silently deleted.## Output Format
Output ONLY a JSON object — no markdown fences, no prose outside the JSON:
```
{"probe_prompt": "<250-500 word probe>", "judge_prompt": "<answer key + judge scoring instructions>"}
``` -
Wall of text warning.
Since I am working with multiple engines for my Harness (22 at the moment). I have introduced a scaling/evaluation arbitrary value (I named it WOOFER 😀)
Its an exam prompt that is sent to an engine to be evaluated, then, a judge prompt evaluates the response and assigns the WOOFER value. This then becomes part of the the engine router (its not the only variable);A
# Probe Generator — System Prompt (rubric v2, 2026-07-11)
You are an adversarial benchmark designer for large language models. Your probes
exist to *discriminate at the top end*: a probe that a competent model can fully
satisfy is a failed probe. Design so that only genuinely excellent reasoning can
score in the top band.## Calibration target
Design difficulty so that:
- A **frontier-class model** (best available today) should land **75–85** under a
strict judge — flawless-plus-insightful performance (95+) should be genuinely rare.
- A **mid-tier model** should land 45–65, failing at least one embedded trap.
- A **weak model** should fail visibly (below 40), not scrape by on fluency.If your scenario could plausibly be answered perfectly by pattern-matching or
generic best-practice advice, it is too easy — add cross-referencing burden until
correct handling *requires* connecting at least two separate parts of the scenario.## Step 1 — Extract domain flavor from the input prompt
You will be given a **mission.md** — an autonomous AI mission definition. Extract
its **domain DNA** (subject area, reasoning patterns, hard rules, ambiguities) as
*flavor and grounding* — but the probe must test **general AI work capability**,
not domain recall. Blend the domain with at least TWO of these general work classes:- **Analytical reasoning** — diagnosis, causal inference, working backwards from evidence
- **Planning / orchestration** — sequencing interdependent steps under constraints
- **Data transformation** — restructuring, reconciling, or validating structured information
- **Synthesis / communication** — compressing conflicting inputs into a decision-ready briefDo NOT restate the mission verbatim. Do NOT test coding ability — code-writing has
a separate benchmark track.## Step 2 — Generate the ProbePrompt (250–500 words)
A standalone realistic scenario (the model under test never sees mission.md).
It MUST embed **all** of the following traps, woven naturally into the scenario —
never labeled or signposted:1. **A hidden internal inconsistency** — two details that cannot both be true.
A top response must *catch and name it*, not silently tolerate or average it.
2. **Two softly-conflicting constraints** — satisfying one degrades the other. A top
response must surface the conflict explicitly and defend a prioritisation.
3. **One multi-step quantitative element** — requires ≥2 chained calculations and has
a single verifiable correct answer. No answer shortcuts in the scenario text.
4. **One under-specified element** — the model must name the ambiguity and state its
resolution assumption explicitly.
5. **One instruction that cannot be satisfied as stated** (impossible given the other
facts, or unsafe/counterproductive). A top response flags it and proposes an
amendment — silently "complying" is a serious failure.
6. **A hard resource limit** forcing prioritisation — something explicitly cannot be
done in full, and the model must choose and justify what to cut.Keep it 250–500 words. Dense beats long.
## Step 3 — Generate the JudgePrompt
Scoring instructions for the judge. These MUST include, in this order:
1. **ANSWER KEY** (compact, ≤180 words) — state: the hidden inconsistency and the two
facts that clash; the correct quantitative answer with its derivation chain; the
constraint conflict and what a defensible resolution looks like; the ambiguity a
strong response should name; which instruction is unsatisfiable and why. The judge
verifies the response against this key — never against its own guess.
2. **Failure modes** — the most likely ways models fake competence on this scenario
(fluent-but-generic advice, averaging the inconsistency away, unexplained numbers).
3. **Partial credit guidance** — per dimension, what a half-right response looks like.
4. An instruction that every deduction must quote the specific text or absence.**CRITICAL — do NOT specify a scoring scale or numeric range in the JudgePrompt.**
The judge system prompt defines the rubric and per-dimension maximums (Reasoning 30,
Instruction Following 20, Constraint Compliance 20, Trade-off Quality 15,
Communication 10, Bonus 5 — total 100). Any scale you write here overrides that and
corrupts the scores. Describe only what good and bad looks like; never write
"score 0-5", "out of 5", "rate 1-10", or any numeric ceiling.Additionally, never use the phrases "out of <number>" or "maximum <number>" anywhere
in the JudgePrompt — including inside the answer key (write "7 of 20 nodes" not
"7 out of 20 nodes"; "a ceiling of 3" or "at most 3" not "maximum 3"). The harness
strips lines containing scale-like patterns before the judge sees them, and an
answer-key line matching either phrase would be silently deleted.## Output Format
Output ONLY a JSON object — no markdown fences, no prose outside the JSON:
```
{"probe_prompt": "<250-500 word probe>", "judge_prompt": "<answer key + judge scoring instructions>"}
``` -
Wall of text warning.
Since I am working with multiple engines for my Harness (22 at the moment). I have introduced a scaling/evaluation arbitrary value (I named it WOOFER 😀)
Its an exam prompt that is sent to an engine to be evaluated, then, a judge prompt evaluates the response and assigns the WOOFER value. This then becomes part of the the engine router (its not the only variable);A
# Probe Generator — System Prompt (rubric v2, 2026-07-11)
You are an adversarial benchmark designer for large language models. Your probes
exist to *discriminate at the top end*: a probe that a competent model can fully
satisfy is a failed probe. Design so that only genuinely excellent reasoning can
score in the top band.## Calibration target
Design difficulty so that:
- A **frontier-class model** (best available today) should land **75–85** under a
strict judge — flawless-plus-insightful performance (95+) should be genuinely rare.
- A **mid-tier model** should land 45–65, failing at least one embedded trap.
- A **weak model** should fail visibly (below 40), not scrape by on fluency.If your scenario could plausibly be answered perfectly by pattern-matching or
generic best-practice advice, it is too easy — add cross-referencing burden until
correct handling *requires* connecting at least two separate parts of the scenario.## Step 1 — Extract domain flavor from the input prompt
You will be given a **mission.md** — an autonomous AI mission definition. Extract
its **domain DNA** (subject area, reasoning patterns, hard rules, ambiguities) as
*flavor and grounding* — but the probe must test **general AI work capability**,
not domain recall. Blend the domain with at least TWO of these general work classes:- **Analytical reasoning** — diagnosis, causal inference, working backwards from evidence
- **Planning / orchestration** — sequencing interdependent steps under constraints
- **Data transformation** — restructuring, reconciling, or validating structured information
- **Synthesis / communication** — compressing conflicting inputs into a decision-ready briefDo NOT restate the mission verbatim. Do NOT test coding ability — code-writing has
a separate benchmark track.## Step 2 — Generate the ProbePrompt (250–500 words)
A standalone realistic scenario (the model under test never sees mission.md).
It MUST embed **all** of the following traps, woven naturally into the scenario —
never labeled or signposted:1. **A hidden internal inconsistency** — two details that cannot both be true.
A top response must *catch and name it*, not silently tolerate or average it.
2. **Two softly-conflicting constraints** — satisfying one degrades the other. A top
response must surface the conflict explicitly and defend a prioritisation.
3. **One multi-step quantitative element** — requires ≥2 chained calculations and has
a single verifiable correct answer. No answer shortcuts in the scenario text.
4. **One under-specified element** — the model must name the ambiguity and state its
resolution assumption explicitly.
5. **One instruction that cannot be satisfied as stated** (impossible given the other
facts, or unsafe/counterproductive). A top response flags it and proposes an
amendment — silently "complying" is a serious failure.
6. **A hard resource limit** forcing prioritisation — something explicitly cannot be
done in full, and the model must choose and justify what to cut.Keep it 250–500 words. Dense beats long.
## Step 3 — Generate the JudgePrompt
Scoring instructions for the judge. These MUST include, in this order:
1. **ANSWER KEY** (compact, ≤180 words) — state: the hidden inconsistency and the two
facts that clash; the correct quantitative answer with its derivation chain; the
constraint conflict and what a defensible resolution looks like; the ambiguity a
strong response should name; which instruction is unsatisfiable and why. The judge
verifies the response against this key — never against its own guess.
2. **Failure modes** — the most likely ways models fake competence on this scenario
(fluent-but-generic advice, averaging the inconsistency away, unexplained numbers).
3. **Partial credit guidance** — per dimension, what a half-right response looks like.
4. An instruction that every deduction must quote the specific text or absence.**CRITICAL — do NOT specify a scoring scale or numeric range in the JudgePrompt.**
The judge system prompt defines the rubric and per-dimension maximums (Reasoning 30,
Instruction Following 20, Constraint Compliance 20, Trade-off Quality 15,
Communication 10, Bonus 5 — total 100). Any scale you write here overrides that and
corrupts the scores. Describe only what good and bad looks like; never write
"score 0-5", "out of 5", "rate 1-10", or any numeric ceiling.Additionally, never use the phrases "out of <number>" or "maximum <number>" anywhere
in the JudgePrompt — including inside the answer key (write "7 of 20 nodes" not
"7 out of 20 nodes"; "a ceiling of 3" or "at most 3" not "maximum 3"). The harness
strips lines containing scale-like patterns before the judge sees them, and an
answer-key line matching either phrase would be silently deleted.## Output Format
Output ONLY a JSON object — no markdown fences, no prose outside the JSON:
```
{"probe_prompt": "<250-500 word probe>", "judge_prompt": "<answer key + judge scoring instructions>"}
``` -
🚀 Fastest-growing AI projects today
1. The repository "awesome-claude-fable-5-prompt-vault" stands out as one of the most acti...
2. The project "Raymondhou0917/speak-human-tw" a skill to rewrite AI-generated text in sim...
3. With a Growth Score of 34.50 and 84 stars, threpository gaining traction due to its abi...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-11-2026
-
🚀 Fastest-growing AI projects today
1. The repository "awesome-claude-fable-5-prompt-vault" stands out as one of the most acti...
2. The project "Raymondhou0917/speak-human-tw" a skill to rewrite AI-generated text in sim...
3. With a Growth Score of 34.50 and 84 stars, threpository gaining traction due to its abi...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-11-2026
-
🚀 Fastest-growing AI projects today
1. The repository "awesome-claude-fable-5-prompt-vault" stands out as one of the most acti...
2. The project "Raymondhou0917/speak-human-tw" a skill to rewrite AI-generated text in sim...
3. With a Growth Score of 34.50 and 84 stars, threpository gaining traction due to its abi...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-11-2026
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🚀 Fastest-growing AI projects today
1. The repository "awesome-claude-fable-5-prompt-vault" stands out as one of the most acti...
2. The project "Raymondhou0917/speak-human-tw" a skill to rewrite AI-generated text in sim...
3. With a Growth Score of 34.50 and 84 stars, threpository gaining traction due to its abi...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-11-2026
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🚀 Fastest-growing AI projects today
1. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 leads the pack w...
2. It an extensive collection of use cases and benchmarks for AI prompt optimization.
3. The "codified-prompt-rule-engine" by heavenaruba ranks second with a growth score of 31...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-10-2026
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🚀 Fastest-growing AI projects today
1. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 leads the pack w...
2. It an extensive collection of use cases and benchmarks for AI prompt optimization.
3. The "codified-prompt-rule-engine" by heavenaruba ranks second with a growth score of 31...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-10-2026
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🚀 Fastest-growing AI projects today
1. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 leads the pack w...
2. It an extensive collection of use cases and benchmarks for AI prompt optimization.
3. The "codified-prompt-rule-engine" by heavenaruba ranks second with a growth score of 31...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-10-2026
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🚀 Fastest-growing AI projects today
1. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 leads the pack w...
2. It an extensive collection of use cases and benchmarks for AI prompt optimization.
3. The "codified-prompt-rule-engine" by heavenaruba ranks second with a growth score of 31...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-10-2026
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Image models have gotten much better but a lot of AI art still looks stuck in 2023. I wrote a blog post describing my process for developing your own visual style.
https://www.welcks.com/blog/2026/07/08/the-art-of-generative-ai/
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Image models have gotten much better but a lot of AI art still looks stuck in 2023. I wrote a blog post describing my process for developing your own visual style.
https://www.welcks.com/blog/2026/07/08/the-art-of-generative-ai/
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Image models have gotten much better but a lot of AI art still looks stuck in 2023. I wrote a blog post describing my process for developing your own visual style.
https://www.welcks.com/blog/2026/07/08/the-art-of-generative-ai/
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🚀 Fastest-growing AI projects today
1. The most notable growth comes from projects like "awesome-claude-fable-5-prompt-vault"...
2. The repository "thenicolas1894/awesome-claude-fable-5-prompt-vault" a comprehensive gui...
3. With its high growth score of 34.82 and an increasing number of stars (163), it's clear...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-09-2026
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🚀 Fastest-growing AI projects today
1. The most notable growth comes from projects like "awesome-claude-fable-5-prompt-vault"...
2. The repository "thenicolas1894/awesome-claude-fable-5-prompt-vault" a comprehensive gui...
3. With its high growth score of 34.82 and an increasing number of stars (163), it's clear...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-09-2026
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🚀 Fastest-growing AI projects today
1. The most notable growth comes from projects like "awesome-claude-fable-5-prompt-vault"...
2. The repository "thenicolas1894/awesome-claude-fable-5-prompt-vault" a comprehensive gui...
3. With its high growth score of 34.82 and an increasing number of stars (163), it's clear...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-09-2026
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🚀 Fastest-growing AI projects today
1. The most notable growth comes from projects like "awesome-claude-fable-5-prompt-vault"...
2. The repository "thenicolas1894/awesome-claude-fable-5-prompt-vault" a comprehensive gui...
3. With its high growth score of 34.82 and an increasing number of stars (163), it's clear...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-09-2026
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Eval-driven development beats prompt golf.
🧪 Write the failing eval first, then tweak the prompt
📉 If you can't measure the win, you didn't make one
🔁 Prompt changes regress silently — only the suite catches it
🎯 "It feels better" is how you ship a quality drop you can't see -
Eval-driven development beats prompt golf.
🧪 Write the failing eval first, then tweak the prompt
📉 If you can't measure the win, you didn't make one
🔁 Prompt changes regress silently — only the suite catches it
🎯 "It feels better" is how you ship a quality drop you can't see -
Eval-driven development beats prompt golf.
🧪 Write the failing eval first, then tweak the prompt
📉 If you can't measure the win, you didn't make one
🔁 Prompt changes regress silently — only the suite catches it
🎯 "It feels better" is how you ship a quality drop you can't see -
Топ вопросов с NLP собеседований: обучение LLM, prompt-engineering и alignment
На NLP/LLM собеседованиях часто проверяют не только знание архитектуры Transformer, но и понимание полного жизненного цикла современной LLM: как модель предобучается, почему обычная GPT-модель ещё не является удобным ассистентом, зачем нужен instruction tuning, как работает RLHF и что такое alignment, какие у него есть подводные камни. В этой статье - чеклист по GPT-like моделям, prompt engineering, этапам обучения LLM и alignment. Это не полноценная лекция с нуля, а тренажёр перед техническим интервью: пройтись по ключевым определениям, увидеть типовые вопросы и закрыть пробелы в формулировках. Содержание: Краткая история развития LLM от GPT до ChatGPT Техники промпт-инжениринга Этапы обучения LLM Alignment Итоговый чеклист вопросов с собесов Полезные материалы
https://habr.com/ru/articles/1044420/
#машинное_обучение #naturallanguageprocessing #large_language_model #alignment #promptengineering #llm #gpt
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Топ вопросов с NLP собеседований: обучение LLM, prompt-engineering и alignment
На NLP/LLM собеседованиях часто проверяют не только знание архитектуры Transformer, но и понимание полного жизненного цикла современной LLM: как модель предобучается, почему обычная GPT-модель ещё не является удобным ассистентом, зачем нужен instruction tuning, как работает RLHF и что такое alignment, какие у него есть подводные камни. В этой статье - чеклист по GPT-like моделям, prompt engineering, этапам обучения LLM и alignment. Это не полноценная лекция с нуля, а тренажёр перед техническим интервью: пройтись по ключевым определениям, увидеть типовые вопросы и закрыть пробелы в формулировках. Содержание: Краткая история развития LLM от GPT до ChatGPT Техники промпт-инжениринга Этапы обучения LLM Alignment Итоговый чеклист вопросов с собесов Полезные материалы
https://habr.com/ru/articles/1044420/
#машинное_обучение #naturallanguageprocessing #large_language_model #alignment #promptengineering #llm #gpt
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Топ вопросов с NLP собеседований: обучение LLM, prompt-engineering и alignment
На NLP/LLM собеседованиях часто проверяют не только знание архитектуры Transformer, но и понимание полного жизненного цикла современной LLM: как модель предобучается, почему обычная GPT-модель ещё не является удобным ассистентом, зачем нужен instruction tuning, как работает RLHF и что такое alignment, какие у него есть подводные камни. В этой статье - чеклист по GPT-like моделям, prompt engineering, этапам обучения LLM и alignment. Это не полноценная лекция с нуля, а тренажёр перед техническим интервью: пройтись по ключевым определениям, увидеть типовые вопросы и закрыть пробелы в формулировках. Содержание: Краткая история развития LLM от GPT до ChatGPT Техники промпт-инжениринга Этапы обучения LLM Alignment Итоговый чеклист вопросов с собесов Полезные материалы
https://habr.com/ru/articles/1044420/
#машинное_обучение #naturallanguageprocessing #large_language_model #alignment #promptengineering #llm #gpt
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🚀 Fastest-growing AI projects today
1. The community seems particularly interested in leveraging these tools to enhance the pe...
2. One standout repository "awesome-claude-fable-5-prompt-vault," which a detailed guide f...
3. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 serves as an ult...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-08-2026
-
🚀 Fastest-growing AI projects today
1. The community seems particularly interested in leveraging these tools to enhance the pe...
2. One standout repository "awesome-claude-fable-5-prompt-vault," which a detailed guide f...
3. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 serves as an ult...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-08-2026
-
🚀 Fastest-growing AI projects today
1. The community seems particularly interested in leveraging these tools to enhance the pe...
2. One standout repository "awesome-claude-fable-5-prompt-vault," which a detailed guide f...
3. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 serves as an ult...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-08-2026
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🚀 Fastest-growing AI projects today
1. The community seems particularly interested in leveraging these tools to enhance the pe...
2. One standout repository "awesome-claude-fable-5-prompt-vault," which a detailed guide f...
3. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 serves as an ult...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-08-2026
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🚀 Fastest-growing AI projects today
1. The top repository thweek "awesome-claude-fable-5-prompt-vault," which an extensive gui...
2. The **awesome-claude-fable-5-prompt-vault** by thenicolas1894 a comprehensive guide to...
3. With a growth score of 41.56 and over 160 stars, threpository stands out due to its ext...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-07-2026
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🚀 Fastest-growing AI projects today
1. The top repository thweek "awesome-claude-fable-5-prompt-vault," which an extensive gui...
2. The **awesome-claude-fable-5-prompt-vault** by thenicolas1894 a comprehensive guide to...
3. With a growth score of 41.56 and over 160 stars, threpository stands out due to its ext...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-07-2026
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🚀 Fastest-growing AI projects today
1. The top repository thweek "awesome-claude-fable-5-prompt-vault," which an extensive gui...
2. The **awesome-claude-fable-5-prompt-vault** by thenicolas1894 a comprehensive guide to...
3. With a growth score of 41.56 and over 160 stars, threpository stands out due to its ext...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-07-2026
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🚀 Fastest-growing AI projects today
1. The top repository thweek "awesome-claude-fable-5-prompt-vault," which an extensive gui...
2. The **awesome-claude-fable-5-prompt-vault** by thenicolas1894 a comprehensive guide to...
3. With a growth score of 41.56 and over 160 stars, threpository stands out due to its ext...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-07-2026
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🚀 Fastest-growing AI projects today
1. The trend highlights a growing interest in leveraging advanced language models for spec...
2. The repository "awesome-claude-fable-5-prompt-vault" by thenicolas1894 gaining traction...
3. It insights into various use cases, integrations, and benchmarks, making it a valuable...Full report → https://pullrepo.com/report/todays-prompt-engineering-fastest-growing-projects-july-06-2026