How do you build custom AI agents with guardrails?
A builder asks how production agents for regulated work like finance, healthcare, and law are protected against prompt injection and destructive decisions. The practical answer starts with what the agent may never do: least-privilege permissions, hard blocks on dangerous tools, and human approval for anything irreversible, since permissions hold where clever prompts get talked around.
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Tracking token use per agent inside Salesforce
A user running several agents through Copilot into Salesforce can only see total credit use in the digital wallet, not per-agent consumption. The fix is to tag each call with its own key or caller ID before it leaves your side, so usage can be logged against the agent's name instead of hoping the wallet splits the total for you.
Read the source →A full-stack developer's path into AI workflows and agents
A developer with four years of full-stack experience feels left behind by the AI wave and asks for a learning path. The useful advice is to skip the theory pile and build one agent around a workflow you genuinely hate doing, learning tool calls and agent loops as they bite, since one working project makes half the abstract concepts click.
Read the source →What actually breaks when an agent runs a daily publishing loop
Running a daily publishing loop, one user found writing was never the weak point — verification was. The agent once tried to publish specific times and prices it had never checked. The fix is a human gate before anything goes out: no invented prices or times, no false first-person claims, and every factual claim backed by a checked source.
Read the source →Low-cost coding options for agentic work, compared by work done
A user compares sub-$15 monthly coding options for powering an agent and vibe coding, frustrated that every vendor quotes credits or requests without saying what that buys in real daily use. The honest test is finished tasks per dollar: run the same small job on each option for a week and count what got done before the meter ran out.
Read the source →GammaX: confirmed airdrop for a StarkEX perp DEX in beta
GammaX, a perpetuals exchange built on StarkEX and currently in beta, has a confirmed airdrop: sign up to join the testnet whitelist, earn over 3,000 points through easy quizzes, and follow its X account. Entry costs nothing but an email signup, though no token launch date or points-to-token rate has been announced yet.
Read the source →Vid.AI: an AI video SaaS at $50.3k monthly recurring revenue
Vid.AI turns ideas and scripts into ready-to-post videos for creators, charging $39 to $200 a month and acquiring customers through Meta ads and influencers. TrustMRR verified $50,300 in monthly recurring revenue across 750 subscribers on November 4, 2026, with $1.66 million in all-time revenue — though revenue peaked near $90,000 a month in early 2026 and the business is now listed for sale.
Read the source →Meta Business Agent now serves over 2 million businesses a week
Meta says more than 2 million businesses use its Business Agent every week, holding over 30 million conversations with customers inside WhatsApp, Messenger, and Instagram, and larger businesses are now charged on token usage. The numbers are vendor-reported, but they signal real demand for chat-based agents that answer customers, book appointments, and close sales.
Read the source →AWS agents freed about $10 million in frozen billing for Worldwide Express
Three agents on Amazon Bedrock now work billing disputes for a freight company, automating 40 to 50 percent of weekly payment exceptions with under 1 percent error. The backlog of frozen cash fell from $15 million to $4 million in six months, cutting time to cash by four weeks — a vendor case study, but a concrete example of agents paying off in back-office work.
Read the source →Meta paid about $1.2 million in Muse bug bounties
Meta's private bug bounty for Muse, running from April until the agent's September launch, drew over 630 reports, confirmed 64 vulnerabilities, and paid about $1.2 million. The largest award, $300,000, covered a pre-release flaw that exposed conversations and authentication tokens, fixed before launch, while a prompt-injection flaw earned $90,000.
Read the source →A user drives FreeCAD 3D modeling through Muse over MCP
A user connected Muse to a FreeCAD MCP server to design on the FreeCAD software running on their own laptop, starting with a simple cylinder, over Tailscale with strict access controls limited to Muse's IP and one port. It is a user report, not an official Meta announcement, but it shows Muse reaching personal computers through MCP.
Read the source →How to teach AI agents company-specific terms and acronyms
A practitioner asks how to stop agents guessing company-specific acronyms from training data. The practical answer emerging from the thread: a glossary only helps when the agent must check it before answering, and unknown terms should fail loudly instead of being guessed.
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