#aiinsoftwaredevelopment — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #aiinsoftwaredevelopment, aggregated by home.social.
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🇨🇦 Canada's new AI strategy promises a 3% GDP boost by raising business adoption of GenAI from 12% to 60% by 2034.
My worry: adoption of GenAI doesn't make an organization more productive. Dropping it onto a broken process just automates the mess. Measure success by adoption rate and orgs will claim they're "doing AI" to hit the number.
To improve productivity, treat each organization as a system and eliminate the bottleneck.
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🇨🇦 Canada's new AI strategy promises a 3% GDP boost by raising business adoption of GenAI from 12% to 60% by 2034.
My worry: adoption of GenAI doesn't make an organization more productive. Dropping it onto a broken process just automates the mess. Measure success by adoption rate and orgs will claim they're "doing AI" to hit the number.
To improve productivity, treat each organization as a system and eliminate the bottleneck.
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🏷️ AI washing: GE promotes Humber River Hospital's command centre as an AI system, but the AI isn't the central feature.
The real value is a cross-disciplinary group paying constant attention to how the hospital works and fixing constraints as they appear. AI helps only because they've studied the flow and set metrics that matter.
The irony? That pattern-finding predates ChatGPT. Flow made the hospital effective, not AI.
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🏷️ AI washing: GE promotes Humber River Hospital's command centre as an AI system, but the AI isn't the central feature.
The real value is a cross-disciplinary group paying constant attention to how the hospital works and fixing constraints as they appear. AI helps only because they've studied the flow and set metrics that matter.
The irony? That pattern-finding predates ChatGPT. Flow made the hospital effective, not AI.
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📉 Losing the skills you stop practising has a name: Deskilling.
In radiology, AI detects abnormalities faster and never tires, but too much reliance leaves the radiologist unable to detect on their own - worse for new doctors who never built the understanding.
Pilots hit this with autopilot and responded with more training, not less. Software is walking the same cliff, but cutting practice instead.
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📉 Losing the skills you stop practising has a name: Deskilling.
In radiology, AI detects abnormalities faster and never tires, but too much reliance leaves the radiologist unable to detect on their own - worse for new doctors who never built the understanding.
Pilots hit this with autopilot and responded with more training, not less. Software is walking the same cliff, but cutting practice instead.
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🃏 GenAI code quality starts with how models are trained. Training rewards pass/fail: does it compile and pass the tests? There's no reward for code that's easy to maintain. Worse, 0-1 grading rewards guessing over admitting uncertainty, so models learn to "bluff" with overconfident guesses.
OX Security likens this to an army of junior developers: fast, functional, lacking architectural judgment. TDD helps, but solves the wrong problem.
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🃏 GenAI code quality starts with how models are trained. Training rewards pass/fail: does it compile and pass the tests? There's no reward for code that's easy to maintain. Worse, 0-1 grading rewards guessing over admitting uncertainty, so models learn to "bluff" with overconfident guesses.
OX Security likens this to an army of junior developers: fast, functional, lacking architectural judgment. TDD helps, but solves the wrong problem.
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🚲 A reader pointed out that no LLM can recommend a trustworthy bike shop. True. And no LLM can do a bike fitting either.
I walked in expecting to buy a $2500 gravel bike. The fitter asked question after question, then steered me to a cheaper one: heavier parts that'll actually last longer. His advice: ride a couple thousand km, see what needs changing, then pay for better.
Embodied, contextual expertise still wins.
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🚲 A reader pointed out that no LLM can recommend a trustworthy bike shop. True. And no LLM can do a bike fitting either.
I walked in expecting to buy a $2500 gravel bike. The fitter asked question after question, then steered me to a cheaper one: heavier parts that'll actually last longer. His advice: ride a couple thousand km, see what needs changing, then pay for better.
Embodied, contextual expertise still wins.
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I shipped a side project with every receipt image publicly exposed. I teach this for a living, I was careful, and I still missed it.
The people being pushed to ship faster with GenAI aren't careless. They're careful people under pressure, with tools that make mistakes easy to create and hard to spot.
Surviving the AI Tsunami is about leading a team that uses GenAI well. Six weeks, real problems from your team. Starts June 29.
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I shipped a side project with every receipt image publicly exposed. I teach this for a living, I was careful, and I still missed it.
The people being pushed to ship faster with GenAI aren't careless. They're careful people under pressure, with tools that make mistakes easy to create and hard to spot.
Surviving the AI Tsunami is about leading a team that uses GenAI well. Six weeks, real problems from your team. Starts June 29.
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A research finding that's easy to miss: GenAI can make people more productive and less motivated at the same time.
More output, less ownership of it. For a Scrum team, motivation and shared understanding aren't nice-to-haves, they're the engine. Trade them for raw speed and it's a poor deal.
A third full: useful for the dull work, oversold on the rest. Protect the conversations that keep people invested.
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A research finding that's easy to miss: GenAI can make people more productive and less motivated at the same time.
More output, less ownership of it. For a Scrum team, motivation and shared understanding aren't nice-to-haves, they're the engine. Trade them for raw speed and it's a poor deal.
A third full: useful for the dull work, oversold on the rest. Protect the conversations that keep people invested.
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🎲 Mandates are landing on desks. Productivity claims are getting louder. Almost no one is bringing the actual research to the conversation.
Three minutes from now you could be the rare person in your org who knows how GenAI actually fails, instead of deciding on vibes.
Test your knowledge of AI Failure Modes in Development Teams.
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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🎲 Mandates are landing on desks. Productivity claims are getting louder. Almost no one is bringing the actual research to the conversation.
Three minutes from now you could be the rare person in your org who knows how GenAI actually fails, instead of deciding on vibes.
Test your knowledge of AI Failure Modes in Development Teams.
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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🐢 "It feels faster" is not the same as "it is faster."
In one study, seasoned devs using GenAI on familiar code came out 19% slower than without it, while certain they were speeding up. Self-reported productivity and measured throughput barely correlate.
A third full: real value, well short of the hype. Measure the real thing, Cycle Time and Throughput, before you trust the feel.
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🐢 "It feels faster" is not the same as "it is faster."
In one study, seasoned devs using GenAI on familiar code came out 19% slower than without it, while certain they were speeding up. Self-reported productivity and measured throughput barely correlate.
A third full: real value, well short of the hype. Measure the real thing, Cycle Time and Throughput, before you trust the feel.
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🥃 Most of the AI conversation gives you two options. The glass is overflowing (AI replaces engineers next year) or empty (all hype, avoid it).
I'd put it at about a third full. GenAI genuinely helps with drudge work, and it'll happily turn a 15-minute task into a 3-hour rabbit hole. Both true.
My course, Surviving the AI Tsunami, helps ScrumMasters and POs tell the real third from the noise. Six weeks, evidence-based. Starts June 29.
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🥃 Most of the AI conversation gives you two options. The glass is overflowing (AI replaces engineers next year) or empty (all hype, avoid it).
I'd put it at about a third full. GenAI genuinely helps with drudge work, and it'll happily turn a 15-minute task into a 3-hour rabbit hole. Both true.
My course, Surviving the AI Tsunami, helps ScrumMasters and POs tell the real third from the noise. Six weeks, evidence-based. Starts June 29.
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🧠 Microsoft researchers (2025) found something uncomfortable: the more confident an LLM sounds, the less critical thinking people apply to what it says.
Confidence is the trap, and only one of the failure modes quietly shaping how teams build software right now.
How well do you know the AI Failure Modes hitting Development Teams? Test yourself.
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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🧠 Microsoft researchers (2025) found something uncomfortable: the more confident an LLM sounds, the less critical thinking people apply to what it says.
Confidence is the trap, and only one of the failure modes quietly shaping how teams build software right now.
How well do you know the AI Failure Modes hitting Development Teams? Test yourself.
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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https://www.europesays.com/people/111939/ Microsoft CEO Satya Nadella has a message for employees: Not every problem needs … #AIInSoftwareDevelopment #AIModels #AITools #ArtificialIntelligence #Microsoft #MicrosoftAIStrategy #MicrosoftCopilot #MicrosoftLeadershipChanges #OpenAI #SatyaNadella
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GenAI has one job: produce a plausible response to your prompt.
Not accurate. Not correct. Plausible.
Plausible is a low bar, and it's the bar the technology is actually optimised for. Every other property is a guardrail or a marketing claim.
Test your knowledge of AI Failure Modes in Development Teams.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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GenAI has one job: produce a plausible response to your prompt.
Not accurate. Not correct. Plausible.
Plausible is a low bar, and it's the bar the technology is actually optimised for. Every other property is a guardrail or a marketing claim.
Test your knowledge of AI Failure Modes in Development Teams.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Ask an LLM why it made a mistake. It does not replay an internal reasoning trace. There isn't one.
It invents a plausible explanation in real time, using the same process that produced the original mistake.
Confidence in the answer is not evidence about the answer.
How many AI Failure Modes in Development Teams can you identify? Test yourself.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Ask an LLM why it made a mistake. It does not replay an internal reasoning trace. There isn't one.
It invents a plausible explanation in real time, using the same process that produced the original mistake.
Confidence in the answer is not evidence about the answer.
How many AI Failure Modes in Development Teams can you identify? Test yourself.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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AI code generators promise speed. The promise leaves out the part where the bill arrives later.
GitClear's data was the first big public signal: copy-paste exceeded moved lines, churn climbed. Several studies since show the same pattern. Code is cheap to write, expensive to maintain.
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AI code generators promise speed. The promise leaves out the part where the bill arrives later.
GitClear's data was the first big public signal: copy-paste exceeded moved lines, churn climbed. Several studies since show the same pattern. Code is cheap to write, expensive to maintain.
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Microsoft 2025 study on knowledge workers and GenAI: the more confident the AI sounded, the less critical thinking users applied.
Interfaces are designed to sound confident. Users are offloading judgment to a system optimised to convince them, not to be right.
Think you know the AI Failure Modes in Development Teams? Test yourself.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Microsoft 2025 study on knowledge workers and GenAI: the more confident the AI sounded, the less critical thinking users applied.
Interfaces are designed to sound confident. Users are offloading judgment to a system optimised to convince them, not to be right.
Think you know the AI Failure Modes in Development Teams? Test yourself.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Security defects in AI-authored code: roughly 1.57x the rate of human-authored.
The models trained on whatever code was on the internet. Vulnerabilities and all. They learned the average, not the secure subset.
More AI code = more AppSec load. Nobody put that on the board.
Test your knowledge of AI Failure Modes in Development Teams.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Security defects in AI-authored code: roughly 1.57x the rate of human-authored.
The models trained on whatever code was on the internet. Vulnerabilities and all. They learned the average, not the secure subset.
More AI code = more AppSec load. Nobody put that on the board.
Test your knowledge of AI Failure Modes in Development Teams.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Heavy AI-adopting teams: change failure rates up ~30%. Incidents per pull request up 23.5%.
Speeding up code generation didn't speed up delivery, it just moved the queue downstream into review, testing, and incidents. Theory of Constraints called this out decades ago.
How much of this is on your radar?
Think you can spot the AI Failure Modes in Development Teams? Test yourself.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Heavy AI-adopting teams: change failure rates up ~30%. Incidents per pull request up 23.5%.
Speeding up code generation didn't speed up delivery, it just moved the queue downstream into review, testing, and incidents. Theory of Constraints called this out decades ago.
How much of this is on your radar?
Think you can spot the AI Failure Modes in Development Teams? Test yourself.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Cognitive Complexity in agent-assisted repositories has been observed to rise 39%. Static analysis warnings rose with it.
Code that's harder to read is harder to change. Slower future work, more incidents. The bill arrives later, not in the sprint where AI sped you up.
How well do you know the AI Failure Modes hitting Development Teams? Test yourself.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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Cognitive Complexity in agent-assisted repositories has been observed to rise 39%. Static analysis warnings rose with it.
Code that's harder to read is harder to change. Slower future work, more incidents. The bill arrives later, not in the sprint where AI sped you up.
How well do you know the AI Failure Modes hitting Development Teams? Test yourself.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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AI agents promised faster delivery. They also delivered 39% more Cognitive Complexity and 30% more static analysis warnings.
A reinforcing loop: more AI code -> complexity rises -> debt accumulates -> velocity drops -> teams write even more AI code to compensate.
Speed gains? Gone within months. Not a tooling problem, a systems problem.
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AI agents promised faster delivery. They also delivered 39% more Cognitive Complexity and 30% more static analysis warnings.
A reinforcing loop: more AI code -> complexity rises -> debt accumulates -> velocity drops -> teams write even more AI code to compensate.
Speed gains? Gone within months. Not a tooling problem, a systems problem.
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AI-generated code: about 1.7x more issues per pull request than human code. At the 90th percentile of teams, that doubles.
Code is cheap to generate. Reviewing and refactoring it is not. The bottleneck didn't move, it just got buried under more PRs.
Test your knowledge of AI Failure Modes in Development Teams. Twelve questions, three minutes.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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AI-generated code: about 1.7x more issues per pull request than human code. At the 90th percentile of teams, that doubles.
Code is cheap to generate. Reviewing and refactoring it is not. The bottleneck didn't move, it just got buried under more PRs.
Test your knowledge of AI Failure Modes in Development Teams. Twelve questions, three minutes.
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
-
Cognitive Complexity in agent-assisted repositories has been observed to rise 39%. Static analysis warnings rose with it.
Code that's harder to read is harder to change. Slower future work, more incidents. The bill arrives later, not in the sprint where AI sped you up.
Test your knowledge of AI Failure Modes Software Development Teams:
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
-
Cognitive Complexity in agent-assisted repositories has been observed to rise 39%. Static analysis warnings rose with it.
Code that's harder to read is harder to change. Slower future work, more incidents. The bill arrives later, not in the sprint where AI sped you up.
Test your knowledge of AI Failure Modes Software Development Teams:
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
-
AI agents promised faster delivery. They also delivered 39% more Cognitive Complexity and 30% more static analysis warnings.
A reinforcing loop: more AI code -> complexity rises -> debt accumulates -> velocity drops -> teams write even more AI code to compensate.
Speed gains? Gone within months. Not a tooling problem, a systems problem.
-
AI agents promised faster delivery. They also delivered 39% more Cognitive Complexity and 30% more static analysis warnings.
A reinforcing loop: more AI code -> complexity rises -> debt accumulates -> velocity drops -> teams write even more AI code to compensate.
Speed gains? Gone within months. Not a tooling problem, a systems problem.
-
AI-generated code: about 1.7x more issues per pull request than human code. At the 90th percentile of teams, that doubles.
Code is cheap to generate. Reviewing and refactoring it is not. The bottleneck didn't move, it just got buried under more PRs.
Test your knowledge of AI Failure Modes for Agile Teams: Twelve questions, three minutes:
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
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AI-generated code: about 1.7x more issues per pull request than human code. At the 90th percentile of teams, that doubles.
Code is cheap to generate. Reviewing and refactoring it is not. The bottleneck didn't move, it just got buried under more PRs.
Test your knowledge of AI Failure Modes for Agile Teams: Twelve questions, three minutes:
#AIinSoftwareDevelopment #BuildInPublic
https://agilepainrelief.com/quiz/ai-failure-modes/?utm_source=mastodon&utm_campaign=archive-reshare
-
Heavy AI-adopting teams: change failure rates up ~30%. Incidents per pull request up 23.5%.
Speeding up code generation didn't speed up delivery, it just moved the queue downstream into review, testing, and incidents. Theory of Constraints called this out decades ago.
How much of this is on your radar?
Edit: missing link: https://agilepainrelief.com/blog/ai-generated-code-quality-problems/
-
Heavy AI-adopting teams: change failure rates up ~30%. Incidents per pull request up 23.5%.
Speeding up code generation didn't speed up delivery, it just moved the queue downstream into review, testing, and incidents. Theory of Constraints called this out decades ago.
How much of this is on your radar?
Edit: missing link: https://agilepainrelief.com/blog/ai-generated-code-quality-problems/
-
Cognitive Complexity in agent-assisted repositories has been observed to rise 39%. Static analysis warnings rose with it.
Code that's harder to read is harder to change. Slower future work, more incidents. The bill arrives later, not in the sprint where AI sped you up.