An AI workflow builder just went read-only
Flowise is frozen and archived. Here is how to decide between freezing, forking, Langflow, and n8n without losing a working AI workflow.
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Technical analysis, model releases, research, and deployment notes.
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346 PUBLISHED ENTRIESOne Reference Image Is Not Enough for GPT Image 2.5
A practical GPT Image 2.5 workflow: use Flare to explore, Sunburst to refine, and assign every reference image one clear job.
Production Agent Failures Belong in CI
Turn failed AI agent runs into regression tests with traces, deterministic scorers, and CI gates that catch prompt, tool, and model regressions before release.
Stop Paying AI Agents to Wait for Work
Use shell checks to poll cheaply and wake coding agents only on failure. This loop-task setup adds max-run limits, logs, and practical guardrails.
RL Training Collapses When Sampler Precision Drifts
Quantized or stale samplers can destabilize LLM reinforcement learning. Score centering targets the drift without replacing sound engine boundaries.
Bash Beats Tool Lists for Strong Coding Models
A 176-setting study shows when coding agents need context management, planning, or predefined tools, and when bash-only is cheaper and better.
Interactive AI Calls Waste Half Your Budget
OpenAI and Anthropic cut batch API prices by 50%. Here is how to decide which AI jobs can wait, calculate the savings, and handle failures.
The Queue Decides When Ollama Stops Being Enough
Ollama is excellent for one user until queue time becomes the bottleneck. Here is a reproducible test for deciding when vLLM is worth the extra deployment work.
Slow Analytics Queries Expose Postgres's Blind Spot
QORL cut a 113-query PostgreSQL workload by 44.7%. The result favors offline plan search, not replacing the database planner.
Most LLM Jobs Do Not Need Your Best Model
A local first Ollama and LiteLLM setup keeps routine LLM jobs private and cheap, while explicit tests and budget caps decide when cloud fallback is allowed.