AI agents automate fund management, eroding enterprise software stickiness

Thursday, July 9, 2026 · from 4 podcasts

The a16z Show This Week in Startups AI Daily Brief Presidio Bitcoin Jam

AI-native firms charge by asset value instead of user seats, creating partnerships to automate $100 trillion in legacy fund administration.
Enterprise software remains entrenched because it codifies business rules, but AI agents shift value from human UI to data access.
The Goose Development Kit aims to become a neutral, model-agnostic framework to prevent vendor lock-in.

A six-day fund migration signals a tipping point. Chris Halanish of Hanover Park told This Week in Startups that AI agents can now ingest decades of legacy documents and map the complex ontology of legal entities and profit allocations, turning a 24-month process into a one-week job. This automation targets the 'human duct tape' system where $100 trillion in global assets relies on manual entry and fragile institutional memory.

"The biggest opportunity is not competing head-on with incumbents but building between established categories using the new technology exclusively."
- Sema Amble, The a16z Show

The shift dismantles the traditional seat-based SaaS model. Hanover Park charges a fee based on assets under management, aligning incentives with growth rather than counting users. This outcome-based pricing reflects a new paradigm where AI-native services own the end-to-end result, not just provide a tool.

Enterprise giants like SAP and Salesforce stay dominant because their software encodes an organization's regulatory compliance and tax rules, not just its data. Steven Sinovsky on The a16z Show argued displacing these systems requires dissolving the business itself, as they are the 'enforcement mechanism' for company operations. AI agents, however, redefine the interaction from workflow to analysis, making the human-centric UI an optional layer.

The Goose Development Kit (GDK) offers a hedge against centralization. Steve Lee on the Presidio Bitcoin Jam said Block donated Goose to the Linux Foundation to create a public-good framework that prevents vendor lock-in with OpenAI or Anthropic. The GDK's Rust API enables dynamic model selection, routing simple tasks to cheap models and reserving frontier models for complex reasoning.

Back-office roles are becoming product builders. Nathaniel Whittemore on The AI Daily Brief argued that when the cost of making drops to near zero, HR and finance professionals will use agentic tools to build custom solutions, turning every department into a hub of 'micro-product' development. The strategic bottleneck shifts from creation to selection, elevating human roles like the Editor and Risk Steward.

Enterprise stickiness is a moat, but AI agents are the bridge.

4 Sources:

The a16z Show This Week in Startups AI Daily Brief Presidio Bitcoin Jam

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Nathaniel Whittemore Steve Lee OpenAI Square Anthropic

Source Intelligence

- Deep dive into what was said in the episodes

The a16z Show

Is Software Losing Its Head? • Jul 7

Seema Amble defines headless software as a trend where the value resides in the underlying data and logic, not the human-centric UI.
Steven Sinovsky identifies three agent tasks: look up data, perform an action, or analyze across systems. Each presents unique challenges like impersonation, seat licensing, and hallucination.
Enterprise software stickiness comes from human UI muscle memory, organizational workflows, being the single source of truth, and the inertia of ongoing payment.
Sinovsky argues the 'stickiest' software often codifies a company's unique business rules, like SAP in an auto manufacturer. Displacing it means essentially dissolving the business.
Amble criticizes the startup misconception that replacing legacy ERP like SAP is just a database and API swap, ignoring the deeply embedded, customized business logic.
Sinovsky recounts Larry Ellison's late-1990s rant that enterprise software was stupid due to customization, advocating an 80% solution that customers rejected.
Sinovsky notes enterprise software's two most used native features are 'export to Excel' and 'export as CSV/PDF,' serving as an escape valve for unmet analysis needs.
Amble states the biggest AI opportunity is not competing head-on with incumbents but building between established categories using the new technology exclusively.
Sinovsky argues that automating a task doesn't shrink the long tail of work; it creates new, more sophisticated tasks and scenarios, like Amazon's post-automation customer service analysis.
Sinovsky observes the primary 'network effect' in enterprise software is viral adoption inside a company, as seen with tools like Excel historically and chat-based AI today.

#Agents #Enterprise #Macro #Startups #Models

This Week in Startups

$100T is managed by "human duct tape" | E2308 • Jul 6

Chris Halanish argues that $100 trillion in global assets is managed by a 'human duct tape' stack where legacy service providers using QuickBooks, Bill.com, and Excel withhold data from funds.
Hanover Park built an AI-native fund administration service, replacing manual accounting with AI agents that learn fund-specific rules to automate financial reporting, capital calls, and data cleaning.
Complex fund structures, like Blackstone’s hundreds of interlinked entities with unique profit allocations, make ledger construction difficult. Traditional migrations could take 24 months, but Hanover Park’s agents completed one for a venture fund in six days.
Chris Halanish states the shift to AI-powered data cleaning and ontology mapping became viable only 3-6 months ago, enabled by OpenAI's Opus model series, moving the industry closer to a 'one-click migration' future.
Hanover Park charges funds a transparent, all-inclusive fee based on AUM, contrasting with legacy administrators that levy hidden per-transaction and hourly rates for services like capital calls.
The company grew from $1B to $20B in AUM over 15 months, scaling its team to 50 people. Halanish focuses on making CFOs 'raving fans' rather than sharing aggregated fund data externally.
Dylan Field explained Figma’s early bottom-up growth strategy, where designers adopted the tool individually and brought it into organizations, easing enterprise adoption and reducing sales friction.
Jason Calacanis described Mahalo’s model of manually curated search pages, which reached $10M annual revenue before Google's Panda update wiped 80-90% of its traffic and abstracted its content into search result one-boxes.
In March 2020, Jason Calacanis predicted a swift COVID recovery, suggesting businesses would reopen by April 15th, while Dylan Field anticipated longer lockdowns and potential enforcement measures.

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The AI Daily Brief: Artificial Intelligence News and Analysis

Nathaniel Whittemore

The Job Positions of the AI Future • Jul 5

Nathaniel Whittemore outlines five new 'work-facing' job archetypes inspired by Boris Cherny: Prototyper generates ideas, Builder makes them production-grade, Sweeper optimizes performance, Grower improves product-market fit, and Maintainer scales mature systems.
Whittemore argues these archetypes reflect a product life cycle. Early-stage teams need Prototypers, Builders, and Sweepers. Growing teams need Builders, Sweepers, Growers, and Maintainers. Mature products need Sweepers, Growers, and Maintainers.
Whittemore adds six 'externally-facing' archetypes missing from Cherny's model: the Editor selects which prototypes to build, the Scout gathers market signals, the Evangelist shapes market perception, the Orchestrator coordinates systems, the Conductor manages agents, and the Risk Steward anticipates operational hazards.
He maps Cherny's five archetypes to sales: the Prototyper tests new pitches, the Builder creates repeatable playbooks, the Sweeper prunes ineffective scripts, the Grower iterates on live strategies, and the Maintainer oversees the sales system.
Whittemore applies the archetypes to marketing. The Scout reads audience culture, the Prototyper tests narratives, the Editor selects brand-fitting angles, the Builder builds campaign machines, the Sweeper kills weak messaging, the Grower optimizes conversions, and the Maintainer upholds brand and CRM systems.
He notes back-office functions like finance and HR may concentrate on Maintainer and Risk Steward roles, with fewer Prototypers, but agentic tools could inject product-building thinking even into these internal domains.
Whittemore believes the core shift is from doing a job to managing agents that execute the work. He argues future-proofing involves becoming the 'maker' or Prototyper for your specific organizational function.
Sponsor Robots and Pencils ships production AI co-workers in 45 days by focusing exclusively on AWS, contrasting with companies that hedge across multiple clouds and frameworks.
Sponsor HyperAgent offers new users $1,000 in inference credits for deploying always-on agent fleets in the cloud that integrate with team tools like CRM and marketing systems.
Whittemore cites the AIDB operators community, which has grown to about 2,500 members discussing organizational development and agentic work.

Also from this episode: (1)

Coding (1)

Sponsor Blitzy's autonomous software development platform delivers over 80% of code autonomously after ingesting an entire codebase, compressing months of engineering work into days.

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Presidio Bitcoin Jam

Open Source AI with Goose & Buzz, New OUSD Stablecoin, Fable 5 is Back • Jul 3

Block developed the Goose AI Agent software over 1.5 years ago, launching it in January 2025, predating many well-known AI agents. Steve notes Block's early leadership in AI, including Jack Dorsey's long-term vision and machine learning acquisitions.
Steve highlights the growing concern over the control and power of frontier AI labs like OpenAI and Anthropic, leading to fears of vendor lock-in, data privacy issues, and potential government intervention.
Goose is designed as a model-agnostic agent harness that can run models in the cloud, locally, or on peer-to-peer networks via Mesh LLM. Mesh LLM, created by McNeil, currently relies on donated compute, with future plans for a payment mechanism.
Goose is pivoting to focus on being a development platform and SDK, releasing a Goose Development Kit (GDK) with a Rust API and bindings for other languages. This GDK will allow developers to build diverse client applications with core Goose components.
The GDK will feature an agent loop for prompt processing, model-agnostic execution, and dynamic model selection to intelligently route tasks to appropriate, potentially cheaper or local, models. This promotes cost efficiency and privacy.
Block donated Goose to the Linux Foundation last year, where it joined the AAIF alongside Anthropic and OpenAI, providing a neutral platform. The six core Goose developers have moved to Spiral, which Steve leads, aiming to apply Spiral's public-good ethos to AI development.
DK uses Buzz to orchestrate multiple AI agents, including Codex, Claude, and Fable, allowing dynamic switching between their specialized personas (e.g., Claude for design, Codex for building). This multi-agent workflow avoids single-interface limitations.
Buzz supports multi-human collaboration, enabling users to lurk, engage, or prompt agents within shared channels, fostering transparent software development from inception. Buzz utilizes Nostr for data storage but can also back data with SQL databases for enterprise needs.
Steve suggests Buzz could become the future community hub for SDKs and APIs, changing developer support by allowing real-time observation and AI-assisted guidance. He envisions a future where individuals can use AI to directly propose and implement app changes.
Steve observes that Claude has become increasingly paternalistic and moralizing in its responses. Conversely, DK finds Fable generally cooperative, easily overriding its safety suggestions during software development tasks.
Steve and DK discuss the concept of recursive self-improvement in AI, noting that while an initial lead could be significant, compute and energy constraints might prevent any single lab from achieving total dominance. Geopolitical factors and robot control could also influence the AI landscape.
Unlike Tether or Circle, OUSD's treasury profits are distributed to value and distribution providers within the consortium, creating a more incentive-aligned system. The stablecoin will be issued on various networks, including Solana, Tron, G. Cole, and Base, with Ethereum conspicuously absent.
MicroStrategy's stock and related equities experienced a price tank, hitting 70-80 cents, but rebounded after policy changes were announced. Saylor corrected a previous misstep by formalizing a minimum 12-month cash reserve (currently $2.5 billion covering 17 months) for debt and dividend payments.
Steve and DK dismiss comparisons of MicroStrategy to Terra Luna as misinformed, emphasizing that MicroStrategy's stock is not a deposit and Saylor is not contractually obligated to pay dividends. Its only long-term bankruptcy scenario involves a flat-to-down Bitcoin price over five to seven years, provided convertible notes still exist.

Also from this episode: (6)

Sports (3)

Steve states the current US Men's National Team is the best ever, showcasing European-level skills under their Argentinian coach. The team won their Wednesday game 2-0 against Bosnia, scoring their first World Cup penalty kick in 32 years.
DK notes the World Cup's expanded 48-team format, up from 32, leading to 12 groups of four teams. The top two from each group and the top eight third-placed teams advance to a 32-team knockout stage.
Steve reports the US will play Belgium on Monday at 5 PM, noting Belgium's recent comeback victory from a 2-0 deficit to win 3-2. The US previously lost to Belgium in the 2014 World Cup.

Protocol (1)

OpenUSD (OUSD) was announced as a new stablecoin backed by a consortium of major financial companies including Visa, MasterCard, Amex, Discover, Coinbase, and Google. This initiative appears to be a direct response to the market presence of Tether and USDC.

Lightning (1)

Lightspark is involved with OUSD, potentially positioning itself to bridge this asset across various intranets to Bitcoin and the Lightning Network. DK suggests that whoever bridges the most networks, especially Bitcoin, will gain a significant market advantage.

BTC Markets (1)

DK believes OUSD poses a greater threat to Circle than Tether, noting Circle's stock dropped 20% on the announcement. He suggests Tether's strong network effect in emerging markets like Latin America and Africa will make it difficult to unseat.

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