TECH Signal 505
Is it all just vapourware?
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An engineer questions whether current AI agent tools are merely vaporware after experiencing usability problems and excessive resource consumption while trying to use them for development tasks.
The critique highlights a growing gap between the promised capabilities of AI-driven agent platforms and their real-world usability, which directly affects engineers who rely on tooling to reduce friction in the software lifecycle. If these tools continue to add overhead instead of removing it, adoption will stall and engineering teams may revert to manual processes or seek alternatives that better integrate with existing workflows. Understanding these shortcomings helps engineers evaluate where to invest time and money in emerging AI tooling.
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The engineer encountered login failures and confusing redirects before gaining access to the ONA platform.
Once connected, the tool rapidly consumed ona compute units while attempting simple task retrieval, providing little productive output.
The author argues that many agentic tools increase rather than decrease the annoying parts of software development, such as integration debugging and token management.
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The engineer’s first interaction with ONA was blocked by authentication problems on the desktop client, forcing a switch to the web version where multiple clicks and redirects were required to log in. This initial friction set a negative tone for the overall experience. The login difficulty illustrates a common barrier where tooling fails to provide a seamless entry point, which can deter engineers from adopting new systems.
After successfully logging in, the engineer linked ONA to a project and observed the tool spending a large amount of ona compute units merely trying to fetch a single task from Linear, without making meaningful progress on the intended workload. The rapid consumption of compute units indicates inefficiency in the agent’s underlying processes, translating to wasted resources for the user. This behavior shows that the tool can generate more work than it saves, undermining its value proposition.
The author points out that many agentic platforms lack systematic review, QA, and usability testing, relying instead on happy-path demonstrations that do not reflect real-world usage. Without rigorous engineering practices, these tools accumulate bugs and usability issues that surface when engineers attempt to integrate them into existing pipelines. Consequently, the promised automation of tedious tasks is often replaced by new sources of friction such as debugging integrations and managing tokens.
Marketing narratives claim that agentic development will let engineers focus on writing code while AI handles the rest, yet the engineer notes that the vendors themselves do not appear to reap the alleged benefits, as their own software remains unpolished. This disconnect between promotional claims and actual product quality suggests that the current ecosystem may be overhyped. For engineers, the takeaway is a need to scrutinize tooling beyond announcements and prioritize solutions that demonstrate proven reliability and low operational overhead in everyday development scenarios.
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