From the meLink team
Category: Agentic AI
-

Liquid D1 Moves Multimodal Decisions to the Edge
Liquid D1 brings compact open-weight decision models to text, vision and audio, giving builders a clearer way to route bounded…
-

AI Retry Design Keeps Agents From Doing It Twice
AI retry design prevents duplicate actions by giving agent workflows stable IDs, clear uncertain states and safe human recovery paths.
-

GPT-6 and Claude Haiku 5.5 Split the Agent Stack
GPT-6 and Claude Haiku 5.5 make a split agent stack practical: richer customer interactions paired with fast, lower-cost supporting work.
-

AI Learning Value Beats Time Saved
AI learning value helps teams choose automation that creates clearer sources, safer routes and reusable operating knowledge, not just faster…
-

AI Revocation Paths Keep Automation Accountable
AI revocation paths let teams withdraw an assistant’s authority safely, preserve useful service, and keep every change accountable.
-

Reflection Beam Open-Weight Model Targets Agents
Reflection AI previews Beam, a 501B open-weight MoE model for agents. The real test begins when its weights and evidence…
-

AI Reference Tasks Cut Through the Demo
AI reference tasks turn glossy demos into evidence: test one real business job, its sources, boundaries, handoffs and recovery.
-

Strata Qwen 3.8 Hits 100 Tokens/Sec Locally
Strata Qwen 3.8 is testing a useful local-AI pattern: sparse routing, private API compatibility and measurable trade-offs before production.
-

AI Friction Logs Turn Stalled Work Into Better Products
AI friction logs turn stalls, corrections and handoffs into a small product-learning loop that improves automation without erasing human judgment.
