AutoGen v0.7.5 adds linear memory support in RedisMemory, enabling more scalable and efficient long‑running agent conversations. It also introduces thinking mode for the Anthropic client and fixes several streaming, tool‑call, and correlation issues that improve reliability and performance for agent builders.
A meta-analysis of 41 papers building on Reflexion-style self-critique loops finds modest, durable gains in coding and tool-use, and diminishing returns in open-ended reasoning.
Compares episodic, semantic, hybrid, and graph-based memory across realistic 30-day agent simulations. Hybrid stores win on recall; graph stores win on cost stability.
An empirical taxonomy of agent tool-use failures across 4,000 traces from production deployments. Schema drift and silent partial-failure dominate.
OpenTelemetry-native LLM observability and evaluation.
Conversational multi-agent framework with strong reasoning patterns.
Hosted, isolated browsers for agent automation with session replay.
Open-source coding-agent IDE extension for VS Code and JetBrains.
Role-based multi-agent framework with declarative crew definitions.
Cloud sandboxes for code-running AI agents.
Pipelines for retrieval-heavy agent workloads.
Lightweight LLM observability with a proxy-first model.
What changed, what matters, what builders should do next. No hype. No paid placement.
Token budgets, fallback tiers, and the dashboards that catch runaway runs before they hurt.
A 90-minute walkthrough that ships a tool-using agent with persistent state, retries, and observability.
How to capture, redact, and score real production sessions to evaluate agent candidates.
A production browser-agent stack with anti-bot resilience, session replay, and a kill switch.
Wire a hierarchical memory store into an existing agent and audit what it remembers.
How leading B2C teams are reducing tier-1 ticket volume by 35-55% with a tightly-scoped support agent.
A research agent assembles a 1-page brief 30 minutes before every external call.
How platform teams replace one-off internal dashboards with a shared agent over their API graph.
A focused agent flags deviations from a playbook and proposes redlines for a human to approve.
An agent enriches and triages SOC alerts, halving the load on tier-1 analysts.