Can a Computer-Use Agent Safely Operate Your Legacy ERP?
Computer-use agents can click through legacy ERP clients with no API. Let them query and save drafts; keep posting and master data edits behind human approval.
Baize AI Notes
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Computer-use agents can click through legacy ERP clients with no API. Let them query and save drafts; keep posting and master data edits behind human approval.
Run a private Codex gateway on official API keys: deploy LiteLLM with Docker Compose behind HTTPS, issue one key per employee with budgets, and log usage.
When natural-language data queries return two different sales figures, the fix is a governed metric dictionary the model must check before it writes SQL.
A recruiting agent speeds up resume screening, but rejected candidates should not be archived unseen. Set up borderline spot checks, appeals, and audit logs.
Factories and construction sites use AI safety inspection to capture on-site hazards. The algorithm captures risk images. A safety officer verifies, grades, and assigns each case. The responsible team fixes it by the deadline, and the officer closes it after an on-site recheck.
When AI visual inspection lets a defect through, saved images and logs decide who is liable. How to split model and inspector duties and tune manual spot checks.
Companies use bid agents to help prepare tender responses. One mistake on a mandatory clause disqualifies the bid. The agent lists disqualification risks and drafts responses. Commercial and technical staff check each item against the tender documents. People approve the price, the original credentials, and the signed submission.
When AI triages B2B inquiries from WhatsApp, email, and web forms, the lead source field needs fixed rules. Five steps keep channel attribution accurate.
Manufacturers can hand first-pass fault diagnosis to AI. The lasting gain is logging veteran technicians' verified fixes in work orders as searchable knowledge.
A procurement agent's supplier shortlist needs reasons buyers can verify and auditors can trace, tied to certificate dates, report numbers, and delivery records.
Plants hand process data to AI for SPC anomaly detection. When parameters drift, the stop-the-line decision needs a clear split between system and people. The system reads data continuously and suggests causes. Shift leads and quality engineers respond by preset tiers, and people own the stop decision and the restart check.
Agent authentication pairs employee and agent IDs per request and intersects gateway and employee rights to stop shared-account data overreach and audit bypass.
AI agents now read vendor pages, check specs, compare prices, and send inquiries for B2B buyers. Humans still sign off. What a landing page needs for each reader.
Agent evaluation repeats fixed real business tasks, reports pass rate, cost per run, latency and variation, and lists failures. One run cannot justify launch.
Deloitte: 23% of firms use AI agents moderately or more; 74% expected in two years. Only 21% rate governance mature. Four checks without longer approval chains.
Agents on shared workflows belong to the process owner. When the builder leaves, swap credentials, check triggers, clear private memory; if unowned, freeze it.
Agent pilots run on clean data with engineers watching. Production brings messy data, cross-system writes, and real consequences. Five checks before you scale.
AI Agent permissions: ease approval for mail search and summaries; approve sends and calendar edits by default. Fill in a permission table before Always allow.
An AI agent took a wrong action. Stop it and revoke credentials in hour one, roll back by action type, replay the action log, and assign accountability by role.
Test agents in mock companies before CRM access. Tools like Era generate them with mock APIs and MCP endpoints. Retest with real data in staging before launch.
Log agent purpose, builder, owner, systems, credentials, triggers, last run. Tier by data sensitivity and action impact. Disable unowned agents by a deadline.
Agent safety guardrails: completion check; caps on steps, tokens, time, repeat calls and tool error streaks. Limit exits are incomplete; log why and open items.
Agent handoffs may carry malicious external content. Verify originators, limit actions, block internal addresses, and get human approval for high-risk writes.
Agent tool approval: code boundary checks, rule auto-approval, human review. Use arguments; ignore model reasons. Strict write checks. Log approvals and blocks.
Agent access by impact: reads, internal drafts, capped writes; humans approve external actions, payments and irreversible operations; upgrade and revocation rules per tier.
Call counts and active users don't show what an AI agent delivers. Track cycle time, rework rate, tool-switching cost, and agent overlap against team baselines.
An AI bot marking a chat resolved does not clear the ticket. How to split auto-close from human ticket review, as China's GB/T 47746-2026 standard does.
China's GB/T 47746-2026 took effect Sept 1, 2026. AI agents may answer order questions; refunds, discounts, and compensation need human or formal sign-off.
Pricing a consumer AI app starts with who pays. Ben Thompson says OpenAI is retracing Dropbox's path, building ad tracking and enterprise products at once.
Remove the AI from an AI-enhanced system and it still runs, only slower. Remove it from an AI Native system and nothing is left. One test to tell them apart.
Start an AI strategy by picking your role. Amazon is its own first customer, Apple owns the entry point and buys models, Microsoft builds the middle layer.
Microsoft 365 E7 is $99 per user per month, with agent overage billed in Copilot Credits. Usage pricing needs monthly decisions; most budgets are set yearly.
Code and math can be checked instantly; long-cycle work cannot. Rank enterprise AI use cases by feedback loop length. Digital ads already run a closed loop.
Models can make dozens of AI video ads a day; fewer pass brand and platform review. China's labeling rules, Google's AI ad labels, and a pre-scale review gate.
Split one lead list by task when buying AI outbound calling. AI handles bulk reach, screening, and standard Q&A. Humans handle objections, pricing, and closing.
China's AI content labeling rules took effect 2025-09-01. An ad legal ledger needs source, generation process, and license fields, plus who logs each one.
McKinsey's 2025 survey: 88% of organizations use AI regularly, yet most haven't embedded it in workflows. After AI training, redesign one real workflow first.
Answer engines often quote the first paragraph under a question-style H2. Write the full answer in the first sentence, then the reasons and exceptions after it.
An AP agent that runs from invoice matching to payment needs match records, call-back checks on bank changes, duplicate checks, limits, batch review, and recon.
Siege Media data on 116 B2B sites: X vs Y pages correlate most with AI referrals. Lead with a verdict, a decision-axis table, fair trade-offs, stable names.
CISA's acting director uploaded a For Official Use Only contract to public ChatGPT. Consumer plans may train on inputs. Redact names, amounts, and seals first.
To get cited by ChatGPT and Perplexity, allow OAI-SearchBot, PerplexityBot, and Perplexity-User, then give key pages a short answer that crawlers can extract.
Moving Codex from one engineer's side tool into a team's development process means settling four issues - task scope, verification, ownership, and lessons.
How to assign GPT-6.1 Sol, GPT-6 Astra, and GPT-6 Luna to Codex subagents by role, which setting wins, and which reasoning levels each model supports.
Codex and Claude Code spend on personal keys won't match finance. Who reconciles, which log fields to keep, and why only gateway-issued credentials work.
First touches, pricing, key accounts, and unclear context go to a human. Routine follow-ups send by rule, with checks on frequency, opt-outs, and approval logs.
AI writes a site faster, but getting it live and stable still takes engineering discipline. A review of one real Cloudflare Pages launch and how we debugged it.
Connect a GitHub repo, set the build command, and add a custom domain to deploy a static site to Cloudflare Pages for free, with global CDN and free HTTPS.
Move a small team from ad hoc AI use to a dev process where AI takes part in requirements, coding, testing, and review, with written rules everyone follows.
AI coding amplifies the engineering discipline you already have. Five guardrails keep output stable - behavior oracles, types, fast tests, traces, refactors.
Run an enterprise AI pilot in one department on one scored workflow with written go/stop criteria. Giving every employee an AI account first is not a pilot.
AI agents stall in production when company knowledge conflicts or goes stale. Make context reliable, executable, and auditable, one workflow at a time.
Track AI inquiries on a B2B export site in three places: a GA4 AI channel (the floor), hidden form fields, and self-reported source. Tag WhatsApp and email too.
AI handles throughput and humans handle judgment. How developer work moves from writing code to system design, agent orchestration, guardrails, and review.
GBrain, Garry Tan's open-source agent memory system, keeps Markdown in Git as the only source of truth and treats its database as a rebuildable index.
Track GEO in three layers (mention rate, citation rate, recommendation quality), check GA4 and Search Console for outcomes, and sample answers repeatedly.
Graph Engineering sits one layer above Loop Engineering: a loop decides when one agent checks its work and stops; a graph decides which loop runs first.
Before enabling Grok Bot company-wide, decide who gets access, how approvals are enforced, and what the Audit Log and Action Recording each actually capture.
All Grok Bots on one Cursor account share one cloud computer, files and logins included. Each Bot's screen is a work surface, not a security boundary.
Since Aug 26, Grok Bot is in Cursor Pro, SuperGrok, and Cursor Teams. Unlike ChatGPT, it takes a task and keeps working on a cloud computer after you log off.
Hand X brand monitoring to a Bot. Each digest item gets a link, why it matters, and whether a person must decide. Write escalation rules before it starts.
A delivery roadmap that takes an AI idea to a working product, with acceptance criteria at every step. Baize AI designs the path; your team builds the product.
Agents can check IT change requests against configs, runbooks, and schedules. Release approval, change windows, and rollback owners still need human sign-off.
llms.txt is a Markdown index at your site root (llmstxt.org v2, 2026). What to list, how to order links, how it differs from robots.txt, and how to test it.
Third-party MCP servers let agents call code on your network. Check the accounts the servers run under, input paths, authentication, version maintenance and credential rotation.
BeyondMimic tracks human motion on a real humanoid, from cartwheels to sprints. Waypoints, joystick control, and obstacle avoidance still need human-written costs.
Fine-tuning a vertical model on weekly-changing facts bakes in stale data. Connect an enterprise knowledge base (RAG) first, then fine-tune for tone and format.
A voice sales AI agent cannot take back what it says on a live call. Six handoff triggers, four facts to pass to the rep, and how to audit call recordings.
A top search ranking does not mean AI Overviews, ChatGPT, or Perplexity will cite you. AEO tracks citations in AI answers. The missing step is the answer block.
Loop Engineering makes AI check its work before it delivers: plan, execute, observe, correct, repeat. Covers the three loops and the templates they leave.
An LLM API gateway gives all of a company's AI calls one entry point for authentication, routing, rate limiting, audit, model fallback, and cost logs.
When every employee buys their own AI account, nobody can see who uses which model or what data leaves. Companies need one trusted relay or gateway instead.
About 68% of US Google searches ended without a click in early 2026. SEO still matters, but brand, local, and transactional KPIs should replace raw traffic.
A practical guide to third-party LLM router risk, malicious model output, Agent Full Access, credential theft, sandboxing, and self-managed LLM gateways.
What is Grok Bot? Learn how xAI's persistent AI agent uses a cloud computer, real Grok Bot use cases, Skills, Routines, Group Chat, and security approvals.
GLM 5.3 is now available on Baize API. Configure the OpenAI-compatible API for Codex, DeepSeek Harness, and Oh My Pi. New accounts receive $10 in starter credit.
Pick an Unsloth Dynamic GGUF from Apple Silicon unified memory, then run Qwen3.8-27B with Desktop, Studio, or llama.cpp. On 32GB Macs, use UD-Q4_K_XL (~17.9GB).
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