Leave a session idle for an hour, send one prompt, and watch the cost jump. There's a specific reason, and it has nothing to do with your prompt.

Leave a session idle for an hour, send one prompt, and watch the cost jump. There's a specific reason, and it has nothing to do with your prompt.
Automatic model routing sounds great until you see the bill. The engine picks the model, you pay its rate, and you barely get a say.
🧠 More context doesn't always mean better AI.
Long-context systems can improve understanding, but too much context can increase cost, latency, noise and confusion.
The goal: smarter context, not just more context. 🚀
Semantica's strongest idea is that auditability starts before the model answers. If you want a regulator-grade why, you need entity resolution, ontology choices, conflicting facts flagged, and lineage you can query later. Prompt logs are too late. #AIEngineering #DataGovernance
How much context will your workflow need in six months? Compare today’s prompt with likely growth—larger files, tool output, and more instructions—then choose a model with headroom. #LLM #AIEngineering https://temprhq.io/models
96GB of RAM. Still got a kernel panic. Two queues for local-LLM fleets is the rule I learned the hard way. https://praveenlavu.com/dispatch/local-llm-fleet-two-queues #LocalLLM #AIEngineering
Goal drift: how a multi-agent crew ends up solving a different problem
Loop drift is one agent staying busy without getting closer to done.
https://loopandretry.github.io/posts/multi-agent-goal-drift/?ref=bluesky
Building AI agents locally on AWS is reshaping how we deploy and scale AI systems. Recent developments show how to run LLMs in isolated environments and deploy agents with minimal latency. Check out the latest tutorials and insights from the BuildVora team. #AIEngineering #AWS #LocalAI
My coding agent enforced a 20-char username limit with len(). A user with two flag emojis got rejected at 9 visible characters. Each flag is 2 code points. New rule: length limits count graphemes, and every limit gets an emoji test case. #claudecode #ai #aiengineering #buildinpublic
AI Agents don’t just answer. They act.
Goal → Reason → Choose Tool → Take Action → Check Result → Complete Task.
Agents can connect with APIs, databases, web services and business applications to execute multi-step workflows.
Build with @octalchip.
#AIAgents #AgenticAI #AIEngineering
Every log line my coding agent writes is INFO. Counted 2,300 lines from one request in my side project. Two were worth reading. New rule in its instructions: INFO only if I'd act on it at 2am. Everything else is DEBUG. Same request now logs 9. #claudecode #ai #aiengineering #devops #buildinpublic
A model can be great for one-file edits and still struggle with repository-wide analysis. Compare context windows, capabilities, and reference pricing before choosing. #LLM #AIEngineering https://temprhq.io/models
La mejor arquitectura con #LLM suele ser la más pequeña que resuelve el problema.
En esta chuleta: 47 herramientas en 6 capas, de proveedores a bases vectoriales. La clave en #AIEngineering no es conocerlas todas: es saber cuál necesitas y cuándo dejarla fuera.
Google combines AI vulnerability scanning with deterministic AST and call-graph validation, then uses another agent to propose fixes.
Use AI for reasoning. Use deterministic systems for verification.
Audited every package my coding agent added this year. 2 of 38 were GPL, in a closed-source app. It never checks. It picks whatever has the most stars and matches the function name. New rule: license printed next to every install it proposes. #claudecode #ai #aiengineering #indiehackers
Cached input can cost a tenth of raw input, and long sessions are where you cash in. Swap models halfway through and that discount resets to zero.
𝗪𝗵𝗮𝘁 𝗮𝗿𝗲 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗰𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗼𝗳 𝗔𝗜-𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁? => lnkd.in/p/eUCa6ZwD
#AIEngineering #SoftwareEngineering #AIAugmentedDevelopment #GenAI
Tried a small Jev vs LLM experiment for adaptive interviews.
Same 100 synthetic interviews, same inputs, different judge.
Jev: 4.9s median / AUC 0.993
Claude Haiku 4.5: 40.4s / AUC 0.969
results:
github.com/jihnma/lab-j...
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→ https://software-architecture-summit.de/berlin/genai_und_mlops_meistern-berlin-2026/
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