Test a 23GB Flint coding agent before routing real work
A local test plan for a new coding agent: memory, decode speed, sampling, output budget, pass@1 scoring, and web-retrieval failures.
Tools
Hands-on reviews of AI tools, measured against real tasks.
Run this 3-task test before making OpenCode 2.0 your daily harness
Run the same multi-MCP task, second-machine /pair, and background subagent test on old and new versions before switching daily harnesses.
Pilot a self-hosted AI coding agent: IBM Bob checklist
A single-node pilot checklist for self-hosted AI coding agents: verify code residency, model endpoint, BYOL terms, air-gap, and deployment.
How to decide whether SWE-2 is worth switching to before you commit
Run a baseline before committing, because the benchmark row that matters depends on your ticket queue.
Test an Open-Weight Model on Your In-Flight Coding Task
Snapshot an in-progress coding task, import it into a compatible agent, rerun it on an open-weight model, and diff code, tests, and cost before switching.
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20-Task Test for a Cheap Router Like Fugu Max
Run the same 20 representative agent tasks through your current model and the router, then compare output-token spend, wall time, and failure checks.
15-minute cache-miss test for Fable 5.1 coding agents
Run three to five real coding tasks on the old and new model, then compare success, spend, and cache behavior before repointing.
The GPT-Live-1 interruption test that tells you whether to retire your STT-LLM-TTS chain
A full-duplex voice model only beats a cascaded stack when your own interruption, latency, cost, retention, and fallback numbers say so.
Muse Code: Crash-Replay and Worktrees Check
A five-check harness for judging whether Muse Code survives long refactors, parallel worktrees, and a cheap tier that trains on your code.
Test a Cheaper AI Model: DeepSeek V4 Flash Drop-In Case
A cheaper model is a drop-in replacement only when it survives your task mix, cost, latency, and failure checks.
Same-Price AI Upgrade: Check Token Burn First
A same-price model upgrade can raise task cost when the accuracy gain burns more output tokens or hits a lower ceiling.
Test Muse Spark 1.3's long-context coding claim on your repo
Run a repo-specific probe before making a new coding model your default.
Copilot Sept 28 Flip: 4 Checks for PR Flow and Invoices
Run a four-item admin check before the next Copilot default changes hit your PR flow and invoice.
Audit local AI agents with Geiger
Run a read-only local AI agent inventory, verify evidence paths and capability labels, then test runtime boundaries before trusting agents.
Run this 15-minute pinned-model audit before Copilot's October 2 deprecation breaks your workflow
Migrate pinned GitHub Copilot models before the October 2, 2026 deprecation by checking picker, policy, scripts, agents, and pricing.
10-Minute Desk Test for Meta Glasses
Run five hands-free checks for task output, input, capture light, privacy fail-safe, and call or lookup reliability.
A 5-Point Checklist for Judging Vendor-Bundled AI Coding Assistants Before They Build Your ERP
Run a five-question gate on schema access, promotion control, model switching, audit trail, and cost/time delta versus using the assistant outside the PaaS.
Test Brave Search API for AI Agents
Use a probe for freshness, citations, ranking, latency, and cost before wiring Brave Search API into an AI agent.
Test Claude Code Token-Cut Workflows on TypeScript
Run a repeatable audit of cost, latency, and failure modes before a cheaper Claude Code worker model becomes the team default.
GPT-6 Astra: When a Smarter AI Code Reviewer Pays for Itself
A better AI code reviewer pays for itself only when bug lift, review burden, token cost, privacy terms, and security coverage clear your bar.
Score Agent Memory on Recall, Latency, Cost, and Leakage Before It Owns Your Support Queue
A practical bake-off for support-ops teams to compare agent memory tools on recall, latency, cost, and leakage before production rollout.
Test an AI Semantic Firewall Before It Becomes Your New Single Point of Failure
Run a repeatable live-agent eval for injection, exfiltration, and false positives before putting a semantic firewall in front of production LLM agents.
Build a 5-minute AI research brief from a trending share-price search—and flag what still needs a human
Use a live share-price search to test an AI tool, then separate verified facts, reported risk, and analyst expectation before acting.