{ "story_id": "2180d8bce7667f035e463907e26126ab", "desk": "drm3", "revision": 3, "published_at": "2026-09-03T23:14:42.000Z", "content_hash": "b77be27844f99c9a8c8a78406f4a40969a989a97ccadcb86296285046af3cc71", "hash_basis": "sha256 over `headline\\ndek\\nprose`, plus `\\n` + the canonical citations JSON when any source is placed, plus `\\n#blog` for blogs", "basis": { "headline": "Bengaluru Housing Boom Leaves Rs 40-Lakh Buyers Behind", "dek": "Developers attribute the disappearance of affordable homes in Bengaluru to building economics rather than lack of demand.", "prose": "Developers in Bengaluru state that the disappearance of affordable new homes is less about a lack of demand and more about the economics of building them. [^1]\n\nA housing boom in Bengaluru has led to the unavailability of affordable new homes for buyers. [^2] Buyers in the Rs 40-lakh price range are left without affordable housing options in the current market. [^3] AI agents do not get lost in complex code because they are not bound by human context limits, meaning the signal to refactor never fires automatically. [^4]\n\nExperienced engineering teams are quietly stopping the practice of pushing to rewrite or restructure the gnarliest parts of their systems. [^5] Historically, software modularity and encapsulation were concessions to the limited size of human working memory, allowing developers to reason about systems in isolation. [^6] The author warns that the failure mode is not bad code from agents, but humans losing the ability to police the code because they no longer understand it themselves. [^7]\n\nThe author asserts that the significant change is that developers can now delegate parts of the engineering loop. [^8] The author states that the biggest shift in software engineering is not that AI can write more code. [^9] The economics of construction are cited as the primary driver for the reduction in affordable housing supply. [^10]\n\nThe article indicates that AI coding agents are changing the landscape of software engineering. 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