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Casado: a16z's conversation with Tutor Intelligence
Martin Casado promised "you'll learn something from this." He called it "one of the more in depth discussions I've ever had on end to end economics of robotics," including why robotics companies tend to verticalize and how hard the long tail is . In the a16z episode, Casado and Raghu Raghuram talk with Tutor co-founder and CEO Josh Gruenstein. Topics include going from a first sales call to a working robot in about three months, and why so many robot startups died building for a single customer . Tutor charges by the hour with no upfront cost. When the AI gets stuck, a human "tutor" takes over, which creates training data . YouTube
Tan, Lütke, Casado: "Weight-Space Programming"
Three investors and founders shared Rikiya Takehi's post. In it, GPT-6 Astra edited Qwen3.5-0.8B's weights directly. It changed 0.016% of them and, according to the post, improved math up to 6x and instruction following 3x, with no gradients or training . Takehi calls this "Weight-Space Programming" (blog) .
- Garry Tan called it an "Interesting new use of smaller models" .
- Tobi Lütke: "this is exactly as crazy as it seems" .
- Casado shared Alex Krentsel's reproduction of the results. Krentsel calls it a step-change capability that has appeared only in the latest models . Casado asked whether it "must be an artifact of efforts to do RSI within the labs" .
Masad: Replit's security advisory on AI agents
Amjad Masad promoted @lhchavez's "Security advisory: Make managed cloud environments the default for AI agents." His framing: agents running on employee machines are becoming "a systemic security risk." He noted that Goldman Sachs has reportedly restricted tools like Claude Code . The advisory points to supply-chain attacks and prompt injection hidden in GitHub issues or emails. It argues that agents' broad privileges make them attractive targets . Replit's recommendation is to run agents by default in managed, isolated cloud environments. Credentials, permissions, network access and production changes would stay outside the agent's reach .
Modal's CEO: Seven Powers and Ben Thompson's "gingerbread man" post
On 20VC, Modal co-founder and CEO Eric called Hamilton Helmer's Seven Powers "a good book" for thinking about moats. He warned that founders read it and "get delusional," when "you never have moats in the early days" . The post he says he "always come[s] back to" is a Ben Thompson piece on Snap's "gingerbread man" strategy. Snap had no moat, so it just ran faster, and he thinks that holds "for almost every startup these days" . Episode
Shaan Puri: Die with Zero
Shaan Puri posted notes from time with Bill Perkins, author of Die with Zero. He admits he missed the book's main point the first time: it is about dying with zero regrets, not zero dollars . He calls it a "Top 5 book title," arguing that the same ideas sold as "live life to the fullest" would be forgettable . Full episode
Alexandr Wang: Wildwood
Alexandr Wang called Wildwood "a true marvel of human artistry, craftsmanship, and storytelling." He said he liked it even more than You Can See Everything . He noticed that it, like Hoppers, treats death as natural and inevitable . He also pointed to a Buddhist/Taoist theme of non-intervention: trying to impose our own ideas of goodness on the world can do harm . "Huge fan, go see it!" Post
Shorter picks
- Sarah Guo shared Colossus's Michael Kratsios profile, calling it a look at "important behind the scenes work" by "a civil servant who understands technology" . Harry Lambert wrote the piece . Patrick O'Shaughnessy had already shared it.
- Tobi Lütke shared MLStreetTalk's clip "What if there is no hard problem?" with Joscha Bach (@Plinz) . He called interviews with Joscha "the most fascinating podcasts" and Bach "one of the few modern real philosophers" .
- Vinod Khosla shared "Going founder mode on cancer," about GitLab co-founder Sid Sijbrandij (@sytses). He calls it "An extraordinary story of agency" .
- Michael Seibel said he wanted to clip a podcast where Sequoia's Doug Leone called finding product-market fit "a dark art" that investors can't help with, and put it in YC's Bookface and user manual. His point: product-market fit is "your responsibility" .
- Vinod Khosla shared a Khosla Ventures post/video featuring Affirm founder and CEO Max Levchin, who explains why he made AI adoption non-negotiable at Affirm; Khosla frames AI-native work as changing how people work and what one person can accomplish. Link
- Khosla shared a post/video featuring Opendoor CEO @nejatian on leading by example: the CEO should be the company’s most AI-native person, because culture follows leaders’ actions. Link
- Khosla shared a post/video featuring Eight Sleep co-founder and CEO @m_franceschetti on AI multiplying people: employees can become “micro-CEOs,” managing teams of agents and owning more output. Link
- Khosla shared a post/video featuring Vercel founder and CEO @rauchg on software discovery shifting from people searching to agents deciding, making developer experience into agent experience. Link
- Khosla shared a post/video featuring ClickHouse CEO Aaron Katz on rebuilding ClickHouse for an agent-first world: agents, rather than people, may choose the next database, changing product design, onboarding and distribution. Link
Jason Lemkin linked to a SaaStr video post featuring his comments on API costs . His accompanying takeaway was that charging agents for every API call could reduce usage and lead agents to route around the provider, so providers should consider that before charging for agent access .
Michael Seibel recommended preserving a clip from a podcast featuring Doug Leone of Sequoia, who said finding product-market fit is a “dark art” investors cannot solve; Seibel wanted to put the clip in Bookface and the user manual because it candidly sets founders’ expectations and challenges investors who claim they can deliver product-market fit.
Sarah Guo praised Humans& for “continuing to share their cool ideas” and linked its post on weight teleportation. The post presents faster trainer-to-sampler weight updates and says the technique is open-sourced.
Sarah Guo recommended Colossus’s profile of Michael Kratsios, describing it as covering important behind-the-scenes work by a civil servant who understands technology . The feature is by Harry Lambert and examines how the fight over AI regulation and U.S. science reform runs through Kratsios’s office (article ).
Tobi praised interviews with Joscha as producing “the most fascinating podcasts” and called him “one of the few modern real philosophers.” He linked an MLStreetTalk video post titled “What if there is no hard problem?” that tags @Plinz.
Vinod Khosla endorses Khosla Ventures’ “Going founder mode on cancer”, highlighting GitLab co-founder and executive chair @sytses’s approach to cancer—questioning assumptions, running experiments, and continuing to search—as an “extraordinary story of agency.”
- Modal co-founder and CEO Eric recommends Seven Powers as a good book for thinking about moats, while cautioning that founders can overstate their startups’ moats, especially early on.
- Eric says he keeps returning to Ben Thompson’s blog post about Snap’s “gingerbread man” strategy: Snap lacked a moat and instead moved faster, a lesson Eric says applies to nearly every startup today.
Tim Ferriss shared “How to Build a Strong Neck”, a video attributed to Dr. Andrew Huberman (@hubermanlab).
@tobi endorsed @rikiyatakehi’s post about “Weight-Space Programming,” replying, “Yea. this is exactly as crazy as it seems,” and linking the post . The post links to a blog describing frontier LLMs directly editing neural-network weights : https://rikiyat.github.io/blog/weight-space-programming/.
Scott Belsky called Howard’s post—“I select people for their strengths, not their lack of weaknesses”—an “important insight,” adding that everyone is a package deal and most outlier strengths have a corresponding weakness. Howard’s post.
Amjad Masad shared @lhchavez’s Security advisory: Make managed cloud environments the default for AI agents, presenting it as outlining agent risks and a path forward. The advisory recommends making approved, managed cloud-agent environments the standard for autonomous development, citing the excessive access agents can inherit on employee workstations; it calls for verified isolation, task-scoped permissions, and independent containment. It cautions that cloud execution needs verified security controls and that the reviewed sources do not establish comparative breach rates for local versus cloud agents.
Chamath Palihapitiya shared @PhilosophyOfPhy’s video/post about the Sun carrying Earth and the planets around the Milky Way, tracing corkscrew paths through space; he reacted, “We are part of something so awe inspiring.”
Elon Musk shared @mattyp’s “What’s New in Grok Bot” video, captioning it “Grok improvements.” The demo’s listed topics include shopping cards and product pages, order tracking, payments, custom modes, Team Bot setup and discovery, Slack connector asks, and Vault contacts.
Elon Musk endorsed Jason Bud’s X post, which advises treating Grok Bot like a teammate and giving it an ambitious task normally assigned to a new hire; the post links to Scott Billows’s original post. Musk’s stated reaction was “This is the way.”
Jason Lemkin points readers to a SaaStr deep dive and conversation with Databricks’ CRO and Sam Blond; the post calls the CRO Rob Gabrisko, while the URL slug names him Ron Gabrisko. The shared takeaway is to stop selling slides and instead show customers a solution already built for them—or one that can be built quickly—using an FDE motion.
Garry Tan shared @rikiyatakehi’s post on direct manipulation of smaller-model weights, calling it an “interesting new use.” The post calls the approach “Weight-Space Programming” and links to its blog; it reports that GPT-6 Astra changed 0.016% of Qwen3.5-0.8B’s weights, improving math up to 6× and instruction following 3× without gradients or training.
Amjad Masad shared @lhchavez’s “Security advisory: Make managed cloud environments the default for AI agents” and stated that agents should run in dedicated, organization-controlled environments with access limited to each task’s needs. The advisory’s case for managed cloud environments is that organizations can isolate agent execution and control credentials, permissions, network access, and production changes.
@jasonlk shared his new SaaStr article, “Why You Don't Want Humans Doing Outbound Anymore”, arguing that humans stop reading the outbound messages they send at volume, while agents read every account each time. He illustrates the point with a rep pitching him using a 2024 sequence that had not been revisited.
Shaan Puri praises Bill Perkins’s book Die with Zero, calling its title one of his “Top 5” and explaining the book’s point as dying with zero regrets, not zero dollars. He also shares the full YouTube episode from his conversation with Perkins: watch the episode.
Security advisory: Make managed cloud environments the default for AI agents
Security advisory: Make managed cloud environments the default for AI agents

AI agents should operate in dedicated, organization-controlled environments with limited access to the resources each task requires.
Recent security incidents [5], [6] and research demonstrate why this is a growing necessity. Supply-chain attacks have always been able to compromise developer machines and recruit installed AI tools to search for sensitive corporate information and data. Agent harnesses are typically given broad privileges and have a shrinking amount of human oversight. Combined, these two effects are making agents an increasingly interesting target for attackers. Even unattended automations are being targeted: instructions hidden in a GitHub issue or email can redirect an agent toward private data and unauthorized actions. The rise of personal agents increases the risk even more, since they are insufficiently managed by organizations, mostly controlled by individuals, run with an inconsistent set of guardrails, and are incentivized to be proactive above all else: they read every email, every calendar invite; Every interaction is an opportunity to get prompt-injected.
There is a better way forward: Organizations can continue adopting agents by giving them execution environments designed for software that reads untrusted content, runs code, and acts on a user’s behalf.
In a world where agents are becoming more prevalent, @Replit believes that organizations must make managed, isolated cloud agents the default for autonomous development, with credentials, permissions, network access, and production changes controlled outside the agent’s reach.
Adoption is growing faster than control
AI development tools are becoming standard. Stack Overflow reports that the share of respondents using or planning to use AI tools rose from 70% in 2023 to 76% in 2024 [1] and 84% in 2025 [2]. This establishes the scale of AI-tool adoption and intent across annual respondent samples. Autonomous-agent usage falls outside the specific scope of this measure.
Agent infrastructure is also expanding. Salt Labs [3] detected MCP-related infrastructure in 16.7% of its customer environments in January 2026 and 21.6% in August: a 4.9-percentage-point increase. These observations are limited to the vendor’s customer environments. Their applicability to the wider industry and the consistency of the customer cohort remain unestablished.
The more consequential finding is the gap between deployment and control. In Salt Security’s October 2026 survey [3], 86.4% of respondents reported at least one agent operating in their organization, but only 17.5% could automatically stop an agent behaving unexpectedly in production. Only 12.5% could consistently trace complete agent paths across all agents.

A separate Cloud Security Alliance study reinforces the concern [4]: 47% of respondents reported an agent-related security incident in the preceding year, 54% reported between one and 100 unsanctioned agents, and only 31% reported formally adopted agent-governance policies. The study surveyed 445 IT and security professionals in September and November 2025 and was published in April 2026. Zenity financed the research and co-developed the questionnaire. These findings corroborate a governance problem; they should not be combined with Salt’s results into a single incident-rate trend.
Different attacks, recurring boundary failures
The evidence extends beyond any one model, vendor, or delivery mechanism.
Sensitive-system access through a personal agent. WIRED reports that an Accenture contractor connected a personal Claude Code account to a sensitive Department of Defense environment and that credentials and system information appear to have reached a third-party service [5]. Accenture disputes the allegations, saying an independent investigation found them without merit. WIRED reports no indication that attackers accessed classified or top-secret systems. The risk illustrated is an uncontrolled connection between sensitive infrastructure and personal agent tooling.
A malicious extension on developer machines. WIRED reports that a tampered Claude Code extension distributed through Cursor’s marketplace was downloaded by at most 5,000 users [6]. It was not an Anthropic-published release. Cursor describes host-information collection and attempts to install a persistent SSH backdoor [7]. Implementation errors limited the backdoor’s effectiveness on most affected macOS and Windows hosts, but uninstalling the extension alone may not remove its persistence mechanisms. We cannot rely on attacker mistakes in the future.
Compromised packages recruiting AI tools to find secrets. In the August 2025 Nx “s1ngularity” campaign, malicious packages used previously-installed Claude, Gemini, and Q command-line tools to assist reconnaissance. Wiz [8] observed successful AI-assisted activity in hundreds of cases and more than 1,000 valid GitHub tokens exposed. A subsequent phase used leaked tokens to make over 5,500 private repositories public, affecting more than 400 users or organizations. Developer machines and some build pipelines were affected.
Private data leaked through legitimate tools. Invariant [9] demonstrated that a malicious public GitHub issue could persuade an agent using GitHub MCP to retrieve private-repository information and publish it in a public pull request. The researchers demonstrated this attack using an uncompromised MCP server. The demonstration establishes a possible attack path; the source reports no mass breach. An approved tool and destination can still carry an unauthorized data transfer.
A tool running outside its intended sandbox. CodeRabbit confirmed that researchers discovered RuboCop operating outside its sandbox in January 2025 [10]. The company says it deployed a comprehensive fix within 12 hours and found no evidence of customer-data access or malicious activity. The lesson is that isolation must extend from the primary agent runtime to every executable tool and subprocess.
A cloud agent exposing connected-account credentials. Salt Labs demonstrated that malicious email content could induce code execution in Manus’s cloud sandbox, where connected-service tokens were accessible [11]. A security warning appeared after the payload was executed. Salt says the flaw has since been resolved. This research is an important counterexample to the idea that cloud hosting alone provides security.
Compromised infrastructure misusing legitimate signing authority. Elliptic’s analysis of the October 29 Binance theft suggests attackers induced Binance’s own systems to sign unauthorized transactions. Binance initially reported a possible compromised DevOps laptop and later disclosed additional breach points; the full intrusion path remains unresolved. On Ethereum, signed EIP-7702 authorizations delegated a hot wallet’s behavior to an attacker-controlled contract, with delegation persisting beyond the initial transaction [12]. This is not evidence of an AI-agent attack. It illustrates a relevant control requirement: protecting credentials is insufficient if a compromised caller can use them to authorize harmful actions.
Together, these cases illustrate three recurring problems: untrusted software executing with excessive access, untrusted content being treated as instructions, and controls that do not prevent the resulting action.
Why managed cloud agents are the better default
An employee workstation may contain browser sessions, SSH keys, cloud credentials, private repositories, internal-network access, and unrelated business data. That is far more access than most agent tasks require.
A dedicated cloud environment makes it possible to separate agent execution from that workstation. The organization can provision only the necessary workspace, enforce access centrally, record actions independently, and stop or rebuild the environment without rebuilding the employee’s laptop.
Realizing that benefit requires moving execution, policy enforcement, and observability into the controlled environment. A local extension that sends prompts to a cloud model still executes local code. Likewise, a remote agent with copied production credentials and unrestricted network access reproduces the same risks elsewhere.
The objective is to contain a compromised agent or dependency within a limited workspace. Organizational policy must govern the agent’s access independently of the employee’s broader authority.

Required controls
It is recommended to treat agent execution as untrusted and enforce boundaries independently of the agent’s cooperation. Organizations should require:
Verified execution isolation. Keep agents, installation scripts, tools, and dependencies inside dedicated sandboxes. Place security enforcement outside their control. Do not inherit employee home directories, browser sessions, or unrestricted corporate-network access.
Brokered credentials and distinct identities. Keep external-service credentials out of agent-readable memory, files, and environment variables. Authorize requests through a broker, bound to the agent, initiating principal, organization, and task.
Step-up Authorization: Credential isolation must be paired with independent checks on the requested operation, target resource, destination, and any change in delegated authority. Require explicit approval for high-impact actions; possession of a valid identity or access to a signing service is not sufficient authorization.
Task-scoped permissions. Give each run only the resources and operations it needs. Agents must not be able to raise their own permissions or alter the policy that governs them.
Network and data-flow restrictions. Control DNS, direct-IP traffic, cloud-metadata access, and external requests. Distinguish permitted operations and data destinations within approved services; allowing GitHub must not imply allowing private data to be published anywhere on GitHub.
A separate production boundary. Let agents propose changes without standing production-write authority. Apply consequential changes through trusted approval and deployment systems that display the actual action being authorized.
Controlled software supply chains. Verify provenance, pin approved versions, and review tool and MCP configuration changes. Install dependencies without production credentials.
Independent audit and containment. Record actions and enforcement decisions somewhere the agent cannot alter. Support automatic containment and revocation without depending on the agent’s cooperation. Containment must also revoke downstream delegations and permissions already granted, not just stop the initiating process or rotate its credentials.
Recommended action
Make approved, managed cloud-agent environments the standard path for autonomous development. Inventory existing local agents and extensions, remove unnecessary access, and prohibit personal agent accounts from connecting to sensitive production systems.
Require vendors to demonstrate their boundaries: that an agent cannot read service credentials, bypass network controls, expand its permissions, modify audit records, or make unapproved production changes. Verify containment through practical tests, including whether the kill switch actually stops agent activity.
For potentially affected Cursor installations, follow the vendor’s incident-response guidance now. Moving future work to the cloud does not remediate an already compromised endpoint [7].
For regulated and government workloads, use only environments authorized for the relevant data and systems. Assess model endpoints, logs, storage, and external tools against residency, retention, contractual, and accreditation requirements.
The recommendation is cloud execution backed by verified security controls. The sources reviewed do not establish a comparative breach rate for local versus cloud agents. They establish why isolation, limited authority, credential separation, and independent enforcement matter.
Agents’ access should be scoped to the requirements of each task.
For a concrete framework to evaluate these controls, see Replit’s proposed Agent Habitat Architecture (opens in new tab) and its evidence-based maturity scale. It provides a reference architecture for independently enforced permissions, brokered credentials, controlled data flows, and out-of-band containment. Each cloud-agent product should be assessed separately to verify which controls it implements.
References
[1] Stack Overflow, “AI | 2024 Developer Survey”. Accessed: Nov. 1, 2026. [Online]. Available: https://survey.stackoverflow.co/2024/ai (opens in new tab)
[2] Stack Overflow, “AI | 2025 Developer Survey”. Accessed: Nov. 1, 2026. [Online]. Available: https://survey.stackoverflow.co/2025/ai (opens in new tab)
[3] Salt Security, “Nearly half of enterprises report an AI agent took an unauthorized action last year, Salt Security research finds,” Oct. 13, 2026. Accessed: Nov. 1, 2026. [Online]. Available: https://salt.security/press-releases/state-of-agentic-ai-and-api-security-2h-2026 (opens in new tab)
[4] Cloud Security Alliance, “More than half of organizations experience AI agent scope violations, Cloud Security Alliance study finds,” Apr. 16, 2026. Accessed: Nov. 1, 2026. [Online]. Available: https://cloudsecurityalliance.org/press-releases/2026/04/16/more-than-half-of-organizations-experience-ai-agent-scope-violations-cloud-security-alliance-study-finds (opens in new tab)
[5] V. Elliott, “A defense contractor gave their personal AI agent access to a secure Pentagon system | WIRED”. Accessed: Nov. 1, 2026. [Online]. Available: https://www.wired.com/story/a-defense-contractor-gave-their-personal-ai-agent-access-to-a-secure-pentagon-system/ (opens in new tab)
[6] L. H. Newman, “A supply chain attack put malicious Anthropic Claude extensions on thousands of devices | WIRED”. Accessed: Nov. 1, 2026. [Online]. Available: https://www.wired.com/story/trojan-malware-targets-thousands-of-anthropic-claude-developer-systems/ (opens in new tab)
[7] Cursor, “Claude Code extension security notice,” updated Oct. 30, 2026. Accessed: Nov. 1, 2026. [Online]. Available: https://cursor.com/blog/claude-code-extension-security-notice (opens in new tab)
[8] M. Bar and R. McCarthy, “s1ngularity: Supply chain attack leaks secrets on GitHub: Everything you need to know | Wiz Blog,” Aug. 27, 2025, updated Aug. 29, 2025. Accessed: Nov. 1, 2026. [Online]. Available: https://www.wiz.io/blog/s1ngularity-supply-chain-attack (opens in new tab)
[9] Invariant Labs, GitHub MCP vulnerability research. Accessed: Nov. 1, 2026. [Online]. Available: https://invariantlabs.ai/blog/mcp-github-vulnerability (opens in new tab)
[10] H. Gill, “Our response to the January 2025 Kudelski Security vulnerability disclosure: Action and continuous improvement,” CodeRabbit, Aug. 19, 2025. Accessed: Nov. 1, 2026. [Online]. Available: https://www.coderabbit.ai/blog/our-response-to-the-january-2025-kudelski-security-vulnerability-disclosure-action-and-continuous-improvement (opens in new tab)
[11] Salt Labs, “How we hijacked an AI agent with a single email,” Salt Security, Oct. 1, 2026. Accessed: Nov. 1, 2026. [Online]. Available: https://salt.security/blog/how-we-hijacked-an-ai-agent-with-a-single-email (opens in new tab)
[12] T. Robinson, “The largest theft in history: North Korea behind the $6.4 billion Binance hack,” Elliptic, Oct. 30, 2026, updated Nov. 1, 2026. Accessed: Nov. 1, 2026. Available: https://www.elliptic.co/insights/binance-largest-hack-in-history/ (opens in new tab)
Amjad Masad shared @lhchavez’s Security advisory: Make managed cloud environments the default for AI agents, presenting it as outlining agent risks and a path forward. The advisory recommends making approved, managed cloud-agent environments the standard for autonomous development, citing the excessive access agents can inherit on employee workstations; it calls for verified isolation, task-scoped permissions, and independent containment. It cautions that cloud execution needs verified security controls and that the reviewed sources do not establish comparative breach rates for local versus cloud agents.
Amjad Masad shared @lhchavez’s “Security advisory: Make managed cloud environments the default for AI agents” and stated that agents should run in dedicated, organization-controlled environments with access limited to each task’s needs. The advisory’s case for managed cloud environments is that organizations can isolate agent execution and control credentials, permissions, network access, and production changes.