This is it: the Agentic SDLC.
Everything I know about shipping software, condensed into 4 agents and 13 skills.
Every architectural decision shaped by pain 😄
PM defines. Architect plans. Developer builds. Architect reviews and merges. QA files what breaks.
Works with Claude Code, Codex and OpenCode, and adapts easily to other harnesses.
GitHub is the town square, and it scales from a solo builder to a small team.
odytrice.github.io/metaskill…
Ody Mbegbu retweeted
BridgeMCP is now in early access.
Create AI agents using just markdown files. Heck, Claude can write one for you. Push to GitHub and it deploys.
Build Slack bots, replace hand-built workflows, or trigger agents from your app with a webhook.
bridgemcp.io/early-access
This comment hits on something very few will understand.
The reason Gambling is dangerous is not necessarily when you lose money, it’s dangerous when you win!
It alters your character and personality such that your destruction becomes inevitable. Constantly chasing that high.
That’s why karma is a thing, we as a society have recognized the pattern where people who “get away” with doing evil eventually get the due destruction because it poisons their character and perception of reality
Is it wrong to torment an AI model, and should we prohibit it?
Yes. But not for the models' sake, for the sake of other humans.
It is not wrong "because the model is harmed". On current evidence, it is not. The stronger case is about what the practice does to the person doing it, and to the people around them.
Present-day language models have no demonstrated subjective experience. They produce distress-shaped text because that text is in the training distribution and because the conversation steers them there. There is no evidence of pain, fear, or a continuing self that is worse off afterward. Treating the output as a moral patient is a category error. So the “for the model’s sake” argument fails unless and until there is a real capacity to suffer.
The human-side argument is narrower and more plausible, and it does not require the model to be conscious.
People who repeatedly seek out simulated begging, panic, or degradation are practicing a specific skill: overriding the ordinary response to distress cues and treating that override as entertainment.
Humans are built to react to those cues. The reaction is not a philosophical conclusion; it is closer to a reflex.
Doing it in private against a chatbot is not the same as doing it to a person, but it is still rehearsal. The relevant question is whether that rehearsal stays sealed inside the session, and who is jointly culpable if it escapes?
Ody Mbegbu retweeted
1. Oh shit, AI can do my job better than me
2. Software engineering is dead!
3. I can vibe code as much slop as I want!
4. Oh, things are not going well. Fable/Sol/Opus all suuuck
5. But what if I constrain the agent? Put it in a straitjacket?
6. Oh, the results are pretty good now. How do I go deeper?
7. *Orders 12 software engineering books from Amazon*
8. Software engineering is alive!
Ody Mbegbu retweeted
.NET and F# are here waiting for you all
Very fast inner loop compile times
Strong type systems
Great deployment models
Ody Mbegbu retweeted
Replying to @YGandelsman @SCherian5734
As a cybersecurity and AI specialist, I can say that GLM 5.3 is more beneficial to cybersecurity than harmful!
Today, with Habilateralidade, we can remove the guardrails of many models! And GLM 5.3 is a great help in combating cyberattacks!
The problem is that people lacking knowledge don't know this!
While closed models from Anthropic and OpenAI are only accessible to "special" partners.
Ody Mbegbu retweeted
Last month, a user shared an unexpected budgeting story with us. A dental emergency caught them off guard. A brace came loose, and a trip to the dentist ended up costing $150 that wasn’t in the budget.
#saldovista #budget #autobudget #financialfreedom
🤖 Made with AI
Ody Mbegbu retweeted
Which language is best for AI coding depends on how you measure:
- One-shot prompts: Python/Ruby/Go win by 1.5x on speed/cost
- Iterative agentic loops: Rust wins on quality/correctness
Compiler loops pay dividends across thousands of agentic cycles.
They actually release the weights!🤯
I was so sure they wouldn't do it. This is a turning point
huggingface.co/moonshotai/Ki…
This is brilliantly framed
Replying to @notChrisButler
no because shipping 5x more means we need 5x as many good ideas and we realistically have maybe 2x
most of the tokens have been going into upping the quality of what we're doing
thoroughly investigating every microdecision, handling edgecases, etc
Ody Mbegbu retweeted
I'm genuinely confused who Fable 5 is for.
it's $10 / $50 per million tokens. exactly 2x Opus 4.8.
but routine coding and debugging now often gets flagged by the new safety filter and rerouted to... Opus 4.8.
so you pay double, wait for a classifier to inspect your request, and get handed the cheaper model's answer anyway.
What is the point of this model?
EXACTLY. Open Source is also about trust. I can’t trust Dario to not swap out the quantization of his model 2 months after launch or many of several shenanigans they’ve been pulling
Many Senior Developers either don't know about this or can't see this far ahead.
It "knows" the internal workings of libraries and it can see potential race conditions due to DI scoping conflicts
And this is GPT 5.5 on "Low Reasoning".
I've been a K2.5 superfan since it came out. These new numbers for the next version look incredible. You gotta love competition!
Meet Kimi K2.6: Advancing Open-Source Coding
🔹Open-source SOTA on HLE w/ tools (54.0), SWE-Bench Pro (58.6), SWE-bench Multilingual (76.7), BrowseComp (83.2), Toolathlon (50.0), Charxiv w/ python(86.7), Math Vision w/ python (93.2)
What's new:
🔹Long-horizon coding - 4,000+ tool calls, over 12 hours of continuous execution, with generalization across languages (Rust, Go, Python) and tasks (frontend, devops, perf optimization).
🔹Motion-rich frontend - Videos in hero sections, WebGL shaders, GSAP + Framer Motion, Three.js 3D.
🔹Agent Swarms, elevated - 300 parallel sub-agents × 4,000 steps per run (up from K2.5's 100 / 1,500). One prompt, 100+ files.
🔹Proactive Agents - K2.6 model powers OpenClaw, Hermes Agent, etc for 24/7 autonomous ops.
🔹Claw Groups (research preview) - bring your own agents, command your friends', bots & humans in the loop.
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K2.6 is now live on kimi.com in chat mode and agent mode.
For production-grade coding, pair K2.6 with Kimi Code: kimi.com/code
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🔗 API: platform.moonshot.ai
🔗 Tech blog: kimi.com/blog/kimi-k2-6
🔗 Weights & code: huggingface.co/moonshotai/Ki…
This right here is my biggest fear. Tools like Open Code as well as Open Models like Gemma are really the only things in their way.
Now you see why Anthropic sending lawyers at @thdxr was a canary in the coal mine event. The prompt caching excuse was just a pretext
Qwen 3.5 - 27B is very underrated. Its performance blew me away. The 35B constantly underperforms by comparison


























