Epictetus
3.4 KiB
aiND Edition — 2026-07-15 (Curated)
Status: HUMAN-APPROVED (8 stories) · staged in entries (curated_by=leonard_aiND, manual_section, manual_tier set)
Not yet on the live webroot — see deployment note at bottom.
Lens applied: build / numbers / outcome / lesson, else scroll.
What People Shipped
Community builds, ships, and earnings — the T1 gold.
Open-Source Local LLM Training Tool (for consumer hardware) (id 2315, T1)
Train/fine-tune local models on consumer GPUs. Install and run today.
→ Do: install it. Run on your hardware.
I Used AI To Sell 10 Websites This Week (id 2648, T1)
A developer shipped 10 client sites with AI help. Concrete paid outcome.
→ Learn: what actually closed deals.
Show HN: I RL-trained an agent that trains models with RL (~$1.3k) (id 2461, T1)
Full build under a hard cost ceiling. Money spent, artifact shipped.
→ Do: replicate the $1.3k training loop.
Benchmarks & Builds
Real numbers, real methods.
I benchmarked 15 "E-Waste" GPUs with Modern Workloads (id 1969, T4)
Cheap-hardware numbers a home-lab operator can compare against.
→ Do: benchmark your junk-drawer GPUs.
GPUHedge: serverless GPU hedging drops cold-start p95 117s → 30s (id 2438, T4)
Measured latency win with a concrete method.
→ Do: steal the hedging pattern for your GPU jobs.
New LLM Coordination Benchmark — Multi-Agent Coordination (id 2441, T4)
A real benchmark with a method.
→ Do: run it against your own multi-agent setup.
Problem Solved
Transferable lessons from the field.
Structured output reliability with LLMs — 3-month production learnings (id 2656, T5)
What held up, what broke, over 90 days of prod.
→ Do: apply the reliability pattern to your agents.
The absolute nightmare of putting AI agents into actual production (id 2645, T5)
What breaks when agents hit prod. A lesson, not a feature.
→ Do: pre-empt the failure modes.
Worth Trying Tonight (highlight)
- Install the Open-Source Local LLM Training Tool
(id 2315)— highest-signal build this window. - Replicate the $1.3k RL-trained agent
(id 2461)— capped cost, full artifact.
Editorial notes
- 8 of 18 reviewed → ~44% of this curated window. The 10 rejects were: PalmClaw (2627), Jacquard (2222), BillAI Bass (2463), NN-in-SQL (2226), Agent-identity (2314), CoT scaling-trap (2444), Upgrade-path (1982), Ford-350 (2649), Codex-encrypt (2157), Ghostcommit (2327).
- Calibration locked: the editor (you) is stricter than the algorithm. Real build / real measurement / real outcome / real lesson — or it scrolls.
- Age: stories ingested Jul 13–14. Not "today," but none were previously posted (recency guard clear). Suitable for a 48h edition.
Deployment note (BLOCKER — not silently worked around)
The live webroot is served by render_site.py / propagate_stack_now.py, which output the legacy "Athena AI News — Clickability" product. They rank by virality and ignore manual_section/manual_tier, so pushing now would either drop these 8 or bury them in a feed that contradicts the aiND brand. Three webroots exist (preprod1/2/3), target unconfirmed.
Next step requires a decision: build a minimal aiND renderer that reads manual_section/manual_tier and emits the sections above (separate from the clickability product), OR confirm the intended webroot. Nothing was pushed to any webroot.