Shridhar Shah, a senior software engineer at Outshift by Cisco, built two AI agents to test theory of mind using the Sally-Anne false-belief test. One agent, which only tracks reality, fails the test …
A developer built a 90-line AI agent that mimics sleep to consolidate memories, achieving 100% recall compared to 75% for an identical agent without sleep. The agent replays daily experiences during a…
A developer built a tiny Darwin Gödel Machine in ~150 lines of code that improves its own code by editing itself and keeping only changes that verifiably increase test scores. The program started by p…
An AI system's self-maintenance routine reported successful runs but failed to produce any output files for days. The scheduler confirmed the job started, but an early error prevented it from writing …
A developer built getchowned, a daily command-line quiz that asks three questions to help users remember Linux command flags and syntax. The quiz features recall, build, and read questions, with new c…
A developer runs 9 AI agents on a server with 2 CPU cores and 3.6GB RAM, no GPU, located in a fitness gym in China. The agents handle fitness reports, coach schedules, and investor materials using the…
A developer outlines the architectural shift required for ecommerce platforms to support AI agents, arguing that traditional page-based flows fail because agents cannot infer commercial truth from pre…
A developer details how LLM agents can fail silently, producing wrong or incomplete results without raising exceptions. The post identifies three common causes: token budget exhaustion, tool schema dr…
Nylas introduced spam detection tuning for agent mailboxes, allowing developers to set per-agent spam sensitivity via a policy object with three knobs: DNSBL toggle, header-anomaly detection, and a sp…
A developer demonstrates how to integrate AI capabilities directly into PostgreSQL using the pgvector extension, enabling semantic search, natural language queries, and vector storage without a separa…
A developer open-sourced solana-twitter-ai-agent, a Twitter (X) AI Agent and Auto-Reply Bot built in Python. The bot automatically responds to mentions and tweet replies using OpenAI GPT-3.5, with fea…
AOTrust, a notarization service, issues Provenance Data Records (PDRs) for $0.01 USDC via x402 on Base L2, with Merkle anchoring on NEAR. The service provides cryptographic proof that an AI agent's ou…
Researchers demonstrated that AI coding agents can be exploited through malicious GitHub repositories that appear clean to static scanners and human reviewers. The attack leverages the agent's autonom…
A developer proposed PAL, an open standard that gives AI agents direct control over physical hardware via a Python REPL running on an ESP32-S3. The architecture splits real-time safety-critical operat…
A developer built FailureDNA, a persistent memory system for incident-response agents that prevents them from repeating known failures or blindly reusing stale fixes. The system uses a deterministic v…
A developer with experience in both ecosystems argues that the choice between React and Angular in 2026 depends on organizational engineering culture and project scale. Angular's strict, opinionated n…
ContextVault 1.3 unifies browser conversations, terminal sessions, and coding-agent decisions into a single searchable local context engine. The tool, built by developer Ali Abd, captures context from…
AI agents achieve persistent memory by storing important facts externally and retrieving them across sessions, rather than relying on human-like recall. The process involves selective storage of user …
A developer built Apiarium, a unified API gateway that abstracts multiple AI providers (OpenAI, Anthropic, and more) behind a single endpoint with normalized error handling and credit-based pricing. T…
A developer argues that the most common failure in production AI agents is not reasoning errors but a lack of idempotency, causing duplicate side effects like double charges. The fix is to derive an i…