Latest Interviews

How To Price For B2B | Startup School

Tom Blomfield

Founders are advised to anchor pricing in a collaborative value equation that quantifies customer ROI, setting rates between 25% and 50% of that value to ensure healthy margins while retaining two-thirds of the benefit for the client. The strategy explicitly discourages cost-plus or predatory price wars, instead urging a shift toward recurring revenue models and short, metric-driven pilots to mitigate revenue volatility. By treating cloud credits as real costs and avoiding public price transparency for enterprise deals, this framework enables startups to secure sustainable growth without triggering a race to the bottom.

Enterprise Sales | Startup School

Pete Koomen, Pete Kuhman

Optimizely co-founder Pete Kuhman outlines a rigorous enterprise sales framework for technical founders, emphasizing that selling before product-market fit requires experimentation with targeted prospecting and personalized outreach. The strategy prioritizes deep discovery during initial calls, uses product-specific narratives to demonstrate value during demos, and treats pricing as a signal of problem severity rather than a fixed metric. By actively managing implementation roadmaps to ensure customer adoption and navigating procurement hurdles with internal champions, founders can transform sales skills into a transferable superpower for fundraising and hiring.

Programming with OCaml's Local Mode | OCaml Unboxed

Jane Street Doe Camel

A Jane Street team member demonstrates practical limitations of the OCaml "Locals" region-based memory management system while optimizing the `best_of_prime_widgets` function to avoid heap allocation. To resolve type mismatches where local lists must escape their regions, the implementation employs a custom zero-overhead `global` wrapper type alongside a recursive map function annotated with `exclave` constraints. Although the solution successfully maintains local allocation for list structures while treating elements as global, the speaker identifies these manual workarounds as sharp corners requiring future improvements through mode polymorphism.

Regions with OCaml's Local Types | OCaml Unboxed

Jane Street researchers introduce a `regional` variant within the OCaml compiler's `locals` feature that treats function parameters as variables permitted to escape their enclosing region exactly once. This mechanism enforces strict type constraints on return values while enabling critical stack allocation optimizations in recursive tail calls and loop iterations. By defining regions around function and loop bodies, the system prevents $O(N)$ space complexity for local data without compromising the language's type safety guarantees.

Exploring the Hidden Secrets within OCaml’s Local Function Types | OCaml Unboxed

Jane Street's OCaml compiler branch enforces strict region safety by automatically inferring hidden `local` annotations on partial applications of functions with local arguments, preventing closures from escaping their intended stack scope. This mechanism triggers compilation errors when such intermediate closures are passed to standard functions like `List.map`, as they attempt to store local data in global heap structures, though these issues can be resolved by fully applying the function or utilizing explicit type expansions. Consequently, the team is considering syntax modifications to function definitions to make these constraints more explicit and prevent accidental region escapes during currying.

Pitfalls with Tail Calls and Locals in OCaml | OCaml Unboxed

Goldfirere

Jane Street researchers developed a "local mode" for their OCaml compiler to optimize memory allocation on the stack, but discovered that standard tail call optimization causes "local value escapes" errors when recursive closures capture variables from a region that ends immediately before the call. To address this, the team introduced a "regional" sub-mode that permits specific values to escape one region boundary, allowing tail-recursive functions to maintain $O(1)$ stack space without explicit `non-tail` annotations, though passing these values through intermediate functions can strip this status and force $O(n)$ allocations. The developers acknowledge that current workarounds like explicit annotations or variable indirection are cumbersome for practical use, prompting a push for better compiler heuristics to automate safe tail calls in future upstream releases.

Stack Allocation with Locals in OCaml | OCaml Unboxed

I

Jane Street is developing an open-source "local mode" branch for the OCaml compiler that reallocates data onto a specialized local stack to eliminate mark-and-sweep garbage collection pauses. By enforcing strict regional scoping where values cannot escape their lifecycle, this architecture enables constant-time deallocation and prevents the cache invalidation and stop-the-world latency inherent in standard heap allocation. The initiative aims to significantly boost low-latency performance by removing the overhead of garbage collection while maintaining memory safety through a novel mechanism called "exclaves."

OCaml Locals Save Allocations | OCaml Unboxed

goldfirere

Jane Street demonstrates how a specialized OCaml compiler reduces memory allocation by introducing the `local` keyword, which restricts value lifetimes to specific function and loop regions. This approach requires replacing standard library functions like `list.iter` with custom implementations that explicitly label arguments as `local` to prevent value escapes, achieving a 50% reduction in word allocations in benchmark tests. Further refinements with the `exclave` keyword and strict type inference drive allocation overhead to near-zero, thereby minimizing garbage collection latency for the experimental feature planned for future upstream integration.

Inferring Locality in OCaml | OCaml Unboxed

The OCaml compiler utilizes an internal allocation discipline that infers local versus global modes for variables and parameters to enable stack-based memory usage and reduce garbage collection overhead. This system prioritizes local inference for arguments while defaulting return values to global to ensure maximum compatibility, with integers serving as a special case that can safely cross mode boundaries under specific annotations. Although this framework enhances performance, current limitations such as standard library functions lacking locality awareness and the need for explicit type signatures to trigger safety checks continue to shape its practical application.

Understanding OCaml Locals as a Mode (with Sub-Moding) | OCaml Unboxed

I

This presentation introduces local and global modes in OCaml as a type system extension that governs memory lifetime and escape properties rather than value structure. The speaker details how these modes enforce safety by preventing local values from escaping their declaration scope while establishing a sub-mode relationship where global values can safely be treated as local. Additionally, the talk outlines four distinct, incompatible function arrow types that strictly regulate argument and result modes to prevent unintended memory escapes, with future work proposed to automate these annotations.

Annotating OCaml Variables and Returns with local_ | OCaml Unboxed

Jane Street is developing an experimental OCaml feature set that enforces strict region constraints through `local` annotations to optimize memory usage and eliminate escaping values. The system introduces the `exclave` keyword to terminate function regions early, enabling specific allocations in the caller's scope while preventing mutable references from capturing local data. Current implementation faces known pitfalls regarding return position rules and compiler error precision, with further refinements planned to address these sharp edges.

Consumer Startup Metrics | Startup School

Tom Blomfield

Founder guidelines for consumer startups define 15% month-over-month growth as the ideal benchmark while emphasizing that viral loops and network effects provide sustainable value compared to paid acquisition. Strategic analysis mandates rigorous tracking of customer acquisition costs against retained users to ensure positive unit economics, alongside defining retention "magic moments" and maintaining a Net Promoter Score above +50 to validate product-market fit. Companies achieving long-term scale typically prioritize an 80:20 split favoring organic channels to mitigate the risks of diminishing returns and platform dependency inherent in over-reliance on paid growth.

Introducing the OCaml Local Mode | OCaml Unboxed

camels

Jane Street is refining the OCaml compiler's type system to introduce a "local mode" feature that enforces function parameters to remain within their execution scope, thereby preventing value escaping. This mechanism guarantees the isolation of mutations and facilitates safer resource management in callback patterns by ensuring local arguments cannot be stored or returned. While the feature remains experimental within the Jane Street branch, it aims to optimize allocation behavior for latency-sensitive code before potential upstream integration.

B2B Startup Metrics | Startup School

Tom Blomfield

This session guides early-stage founders on establishing a rigorous foundational metrics strategy that prioritizes revenue, burn rate, and Net Dollar Retention over vanity data to ensure financial viability. It details how to define consistent unit economics and gross margins, warning that negative unit economics in the current high-interest environment require immediate product or pricing fixes before any scaling efforts. The presentation concludes by balancing these quantitative requirements with the necessity of direct customer interaction, urging leaders to use data to inform decisions rather than replace human empathy and intuition.

How to find the right career for you | The 80,000 Hours career guide (2023 edition)

This presentation challenges the traditional view of career planning by arguing that professional abilities are constructed through practice rather than discovered, using historical data to demonstrate that early performance rarely predicts long-term success. It outlines a scientific method for career selection that replaces unreliable introspection with a hypothesis-driven approach, utilizing a tiered "ladder of tests" to empirically validate personal fit before committing to a path. By prioritizing reversible early experiments and high-upside opportunities, the framework guides individuals to maximize their impact and satisfaction through iterative learning rather than speculative prediction.