🛠️ Tech Trends Brief — May 25, 2026

Open-source AI agent (26,795 ⭐, #1 GitHub trending) by tinyhumansai. Runs fully on-device via Ollama, stores memory encrypted locally with AES-256, one-click connects Gmail/Slack/Telegram/Notion/GitHub.

Private, persistent personal AI that never sends data to the cloud. Second-brain memory across sessions. Full offline inference on hardware you already own.

curl -fsSL https://openhuman.ai/install.sh | sh — connect one service (Gmail or Notion). Use it for 3 days. Compare to ChatGPT/Claude in terms of remembering your context.

Field reps and PMs could run a completely private AI assistant on their MacBooks — no per-token costs, no data leaving the building. Memory that knows your current bid, client preferences, open issues.

Open-source WiFi sensing platform (65,107 ⭐). Turns commodity WiFi signals into real-time spatial intelligence, vital sign monitoring, and presence detection — zero cameras. v0.6.5 ships with $9 ESP32 firmware.

Human pose estimation, breathing rate monitoring, heart rate detection, and presence sensing through walls using WiFi CSI (Channel State Information) data.

Buy a $9 ESP32-CSI node, flash v0.6.5 firmware, run cargo run -p wifi-densepose-sensing-server. Open localhost:3000/ui. Walk around and watch it track your skeleton through a wall.

Job site safety monitoring — detect if someone's in a restricted zone without cameras. Occupancy sensing for building commissioning. Low-cost, privacy-preserving presence detection.

Google I/O 2026 unveiled the biggest change to Search since the search box debuted 25 years ago. The "intelligent search box" expands into AI-powered interactive experiences, dispatches information agents, and lets users build personalized mini apps.

Conversational, agentic search. AI agents dispatched on your behalf for multi-step research. Personalized mini-apps built from natural language queries.

Visit labs.google.com/search and try the new experience. Ask: "What are current lead times for architectural glass from Chinese manufacturers?" Compare depth vs. traditional results.

If clients find your competitors through AI search agents rather than traditional SEO, PGC needs to be listed in those agentic knowledge bases. SEO strategy is shifting from "ranking on Google" to "being cited by AI agents."

GitHub 21,035 ⭐. Pre-indexed code knowledge graph for Claude Code (compatible with Codex/Cursor/Copilot/Gemini CLI). Reduces token usage and tool call counts by 80%+ through semantic indexing.

Token-efficient AI coding. Faster context retrieval across large repositories. Enabling AI agents to reason about entire codebases without running out of context window.

npm install -g codegraph then codegraph index && codegraph query "how does auth work here". Compare tokens used vs. raw Claude Code context.

Token-efficient agents mean cheaper per-query costs for internal tooling. The codegraph pattern also applies to document knowledge graphs — specs, submittals, past bids.

GitHub 9,998 ⭐. Open-source on-device TTS via ONNX, multilingual across 31 languages. Runs entirely on-device — no API calls, no latency, no cloud dependency.

Voice output for AI agents on low-power or air-gapped devices. Accessibility. Multilingual field communication without internet.

pip install supertonic && supertonic --voice "en-US" --text "Your glass order is delayed 48 hours". Test offline on your field tablet.

Field crews needing hands-free updates (delivery status, change orders) could get audio on a tablet without internet. Multilingual support for Spanish-speaking workers.

GitHub 17,132 ⭐. Persistent memory infrastructure for AI agents — Rust-native encrypted storage, semantic search, optional Ollama offline mode.

Building agents that remember across sessions without context-window bloat. Encrypted local brain for personal AI. Institutional knowledge bases.

pip install agentmemory && agentmemory-cli init --profile glazing-bids. Ask it to remember your three biggest competitor markups. Query them a week later.

Bid memory — agent that knows your historical win/loss rates, typical margins on hospital vs. school jobs, standard markup language — persisting across sessions without manual re-prompting.

GitHub 22,078 ⭐. Principles (inspired by Heroku's 12-Factor app) for building, operating, and scaling LLM-powered agents in production. Covers tool use, memory, error handling, observability, and deployment.

Production-grade agent architecture. Best practices for agentic pipelines. Evaluating whether your vendor's agent stack is built for real-world use.

Read the 12-factor agents README. Score your current AI vendor tooling against the 12 factors.

Before buying another AI tool, ask: does it follow these 12 factors? If your "AI assistant" for bid writing lacks retry logic, memory, and observability — it's not production-grade.

GitHub 20,003 ⭐. A stealth browser based on Chromium that passes all known bot detection tests. For legitimate competitive research, market intelligence, and web scraping without blocking.

Anonymous competitive research. Automated data collection from sources that block traditional crawlers. Market intelligence on competitor pricing.

docker run -p 9222:9222 cloakbrowser/chrome. Navigate to a competitor's site. Compare what's visible vs. regular Chrome.

Competitive intelligence: see what competitors are quoting publicly, what products they're promoting, how they position themselves — without triggering anti-bot defenses.

GitHub 92,438 ⭐. All-in-one JavaScript runtime and toolkit. Bundles 3–10x faster than webpack, installs packages 6x faster than npm, runs TypeScript natively.

Fast builds for internal tools. Replacing npm/webpack pipelines. Running server-side JavaScript. SQLite integration. Testing.

curl -fsSL https://bun.sh/install.sh | bash && bun build --target=browser ./src/index.ts. Time it vs. your current webpack build.

If PGC ever builds or maintains internal web tools, Bun's build speed and simplicity could cut dev-ops overhead significantly.

MCP (Model Context Protocol) + A2A (Agent-to-Agent) are emerging as the standardized communication protocols for AI agents. MCP handles agent-to-tool. A2A handles agent-to-agent. MCP hit 97M downloads this period.

Standardized, interoperable AI workflows. One agent triggering another without human intervention. Cross-platform agent ecosystems.

Read the MCP spec at modelcontextprotocol.io and A2A spec on GitHub. Identify one PGC workflow that could be automated if two AI tools could talk directly.

When SAP agents, Microsoft Copilot agents, and PGC's custom agents all speak A2A — workflow automation explodes. This is the layer that makes truly autonomous bid processing possible.

Salesforce's agentic AI platform. 29,000 deals closed since launch. $800M ARR. Agents execute business processes autonomously — CRM updates, quote generation, workflow routing — not just suggest actions.

Autonomous CRM hygiene, automated quote-to-cash, self-executing service workflows.

Request an Agentforce demo. Map one manual process (updating bid status in Salesforce) and see if an agent can own it end-to-end.

If PGC uses Salesforce or any CRM, Agentforce shows what's coming — agents that do rather than recommend. Is your CRM data clean enough to trust an agent with it?

New research (arXiv:2605.00742): orchestration layers for AI agents must be designed per Bayesian decision theory. LLMs are uncalibrated about their own uncertainty. A Bayesian controller only triggers a tool call when Value of Information (VoI) outweighs cost.

High-stakes agentic deployments where wrong actions cost more than asking for clarification. Financial, medical, safety-critical decisions.

Search "arXiv 2605.00742 Bayesian control layer" and read the summary. Apply VoI framework to one PGC decision — like a bid/no-bid recommendation.

When trusting an AI to price a bid, you want it to say when it's uncertain. Bayesian control layers are the theory for making AI know what it doesn't know — critical for high-stakes decisions.

Dell CTO Jeff Clarke: token consumption for AI reasoning is up 320x as agentic systems break cloud economics. Enterprise data center architecture requires complete rethink — you can't run agentic AI at cloud API pricing at scale.

Justification for on-premise and edge AI deployment. Driving local inference adoption, quantized models, and hybrid architectures.

Run one week's worth of team AI queries through cloud API. Calculate actual token spend. Compare to local inference (M-series Mac + Ollama) cost amortized over hardware.

10 people × 50 queries/day × $0.01/query = $5/day = $1,825/year in cloud AI. Local inference (post hardware purchase) is effectively free per query. The math changes fast at scale.

At ServiceNow Knowledge 2026, NVIDIA + ServiceNow announced governed autonomous agents — from employee desktops to AI factories. Governed = audited, role-based, with rollback and approval workflows built in.

Enterprise-grade autonomous agents with the compliance controls regulated industries (construction, healthcare, finance) require.

Request a ServiceNow AI Factory demo. Ask specifically about governance/audit trail features. Compare to PGC bid agent requirements.

PGC operates in a regulated environment with change orders, RFI chains, and subcontractor approvals. Governed agents = productivity of autonomous AI + legal audit trail.

GitHub 7,188 ⭐. Open-source agentic video generation platform with multi-role and scene support. Prompt-driven video with consistent character identity and scene continuity across shots.

AI-generated site documentation, progress video narration, safety training videos, client progress updates — without a camera crew.

pip install vimax && vimax generate --prompt "glass installation crew on curtain wall, morning site, safety vests" — evaluate quality for job site documentation.

Weekly site progress videos, client updates, safety documentation — all AI-narrated, generated from text prompts. No camera crew needed for routine updates.