Why Simple ChatGPT Wrappers Are Losing Value: AI Model Makers Integrate Features, Pushing Startups to Control Full Industry Processes
Early startups that attempted to wrap access to large language models like ChatGPT and sell them as standalone products are quickly losing relevance. Developers of foundational AI systems are now integrating the very capabilities that once formed the core of these young companies' offerings.
According to the venture capital firm NFX, startups should abandon simple overlays on third-party models and instead seize control of entire industry processes. Rather than building narrow tools for lawyers, companies are creating comprehensive AI-powered legal services, and instead of isolated procurement applications, they aim to manage full supply chains.
The first wave of such wrappers emerged shortly after the launch of ChatGPT. These tools generated advertising copy, responded to customers, supported sales teams, and extracted information from legal documents. The companies behind them assumed that base models would remain unable to handle specialized tasks independently for a long time.
That calculation did not hold. OpenAI, Anthropic, and other model developers began transforming their systems into complete working products. Features that assist with programming, document work, and content creation have become native parts of major platforms, stripping smaller single-task companies of their primary differentiation.
One of the most prominent examples is Jasper. In 2022 the company raised $125 million at a $1.5 billion valuation and was viewed as a leader in AI advertising copy generation. It later lowered its annual revenue forecast, reduced headcount, and shifted direction, now attempting to evolve into a full marketing platform.
More durable approaches have come from companies that treat AI as the foundation of an entire service rather than a single feature. The legal platform EvenUp focuses on personal injury cases and has expanded to prepare documents, process case materials, and manage additional workflow stages. NFX reports that more than 2,000 law firms now use the service.
Another example is Blitzy, which builds enterprise software to replace contractor teams. The system analyzes a customer's entire codebase, breaks large projects into smaller tasks, and selects appropriate models for each step, capturing internal dependencies that generic models might overlook without domain-specific preparation.
The mortgage service Tomo has gone further by automating sales, borrower verification, and daily operations. The company states that 77% of its clients receive better interest rates than those offered by traditional mortgage providers, demonstrating a strategy of replacing legacy processes rather than layering new software on top of them.
Seso has adopted a similar model for managing seasonal agricultural workers in the United States. Previously, employee records, visa information, and documentation were scattered across law firms, office software, and paper files. With more advanced models, Seso now also handles transportation, housing, business insights, and personnel decision support.
Large organizations can also integrate AI directly with model developers. The law firm Freshfields, for instance, has partnered with Anthropic to build specialized tools, although such initiatives demand substantial compute spending and dedicated technical staff, and automation remains only one part of their traditional business.
NFX believes younger companies can still win by specializing deeply in narrow niches. Industry expertise, accumulated data, established sales relationships, and control over every stage of a service are significantly harder to copy than isolated software functions. As universal models grow stronger, the value of simple wrappers diminishes, making the ability to convert AI capabilities into complete, operational businesses increasingly critical.
Related articles
OAuth Authorization Server Built Without Storing User Profiles
The article details the evolution of an OAuth Authorization Server that deliberately avoids storing user profiles, relying instead on external identity providers for authentication. It addresses three core constraints: hundreds of dynamically created isolated APIs, a public SPA client without a BFF, and the inability of resources to query the AS on every request. The design separates concerns so the AS handles only clients, tenants, grants, audiences, scopes, keys, sessions, and token issuance while the Main API owns profiles and roles. Tokens are managed securely inside a Service Worker using a custom FedCM grant, eliminating races across tabs and reducing XSS exposure. The approach minimizes blast radius, simplifies compliance, and keeps the AS replaceable without affecting product domain logic.
Why a 202-Character License Key Uses ECDSA P-256 Instead of Ed25519 or RSA
A developer building offline license verification for a .NET desktop application evaluated Ed25519, RSA, and ECDSA P-256 before selecting the last option. The decision was driven by the requirement for zero external dependencies, keys short enough for manual entry from email, and support for key rotation without breaking existing licenses. Although Ed25519 offers faster verification and a smaller public key, it is absent from System.Security.Cryptography in both .NET 8 and .NET 10, with API approval only targeted for version 11. RSA-2048 produces signatures too long for practical use, resulting in a 571-character Base32 string that users would find cumbersome. ECDSA P-256 with SHA-256 delivers a fixed 64-byte signature that becomes a manageable 202-character key when encoded in Base32, while remaining fully available in the runtime. The article also covers performance measurements, the risks of ECDSA nonce generation, and the deliberate choice of the IEEE P1363 signature format to guarantee fixed-length output.
Pilcrow Publishes Free Comprehensive Guide on Web Authentication
Author Pilcrow has released a detailed, ad-free handbook covering authentication and authorization practices for web applications. The resource draws on personal experience and includes practical examples in JavaScript and Go. It examines password-based methods, email verification, multi-factor authentication, passwordless flows, and passkeys while highlighting associated risks and usability trade-offs. The book also provides in-depth guidance on session management, token security, expiration policies, and email address handling as account identifiers. Recommendations emphasize choosing methods that match application security requirements and user expectations. Additional context is given on OWASP resources and community support channels.
redb 3.4.0 Adds Replay Checkpoints, Shared Runtime Layer and Declarative Secrets Handling for .NET Ecosystem
redb 3.4.0 delivers operational improvements for the .NET integration platform that includes typed storage over Postgres, MSSQL and SQLite, the redb.Route engine modeled after Apache Camel, the Tsak runtime with dashboard and clustering, and redb.Identity for OIDC and OAuth 2.1. The release focuses on post-deployment resilience with replay checkpoints that capture message state at named points inside routes, allowing safe re-execution of downstream steps without duplicating side effects. A shared runtime layer moves framework assemblies into a separate Libs/shared directory so that individual DLLs can be replaced without rebuilding or redeploying the entire Tsak or Identity packages. Secrets are now declared with a [Sensitive] attribute on endpoint options, ensuring URIs containing passwords or keys are sanitized before they reach logs, metrics or health checks. Additional controls include role-based access to management APIs, persistent audit trails and cryptographic signing of dynamically loaded modules. All Pro features remain free on the entire 3.x line with no licensing server required.