Prolog Laravel Package

Product Decisions This Supports

• Build vs. buy for rule-based logic: Informs whether to encode business rules (eligibility, pricing tiers, compliance checks, routing) as Prolog predicates inside the PHP application versus adopting a dedicated rules engine or external service.
• Feature scoping for “configurable logic”: Helps decide whether to expose a Prolog-backed rule layer to internal teams or customers, or keep rules as plain PHP/config until complexity justifies a logic engine.
• Roadmap sequencing for expert-system features: Supports prioritization of features like automated decisioning, policy validation, workflow guards, and constraint checking by validating whether an embedded logic engine is viable within the existing Laravel stack.
• Prototyping and feasibility work: Enables fast spikes where product wants to test rule-heavy behavior (e.g., eligibility matrices, fraud heuristics, scheduling constraints) without standing up a separate service or language runtime.
• Architecture and vendor-risk decisions: Provides evidence for choosing between embedded Prolog, a SaaS rules platform, or hand-rolled PHP rules — with explicit tradeoffs around community size, maintenance, and operational overhead.
• Use cases to evaluate: Business rules engines, compliance/policy checks, configuration validators, access-control predicates, recommendation/filtering logic, and educational or internal tooling where declarative logic improves clarity over imperative PHP.

When to Consider This Package

• Consider it when the core product problem is naturally declarative — rules, facts, inference, backtracking, or constraint-style evaluation — and you want it to run inside a Laravel/PHP process rather than as a separate service.
• Consider it when rule sets are small-to-moderate, change frequently, and benefit from being expressed as logical predicates that non-PHP specialists (analysts, domain experts) can inspect and reason about.
• Consider it when you need an embedded engine for prototypes, internal tools, batch jobs, or queue workers where adding a new runtime (SWI-Prolog, Clingo, a rules SaaS) is disproportionate.
• Consider it when the team has Prolog familiarity or is willing to invest in it; otherwise the learning curve will erode the expected productivity gain.
• Look elsewhere when the workload is high-throughput or latency-sensitive: a PHP-hosted WAM implementation is unlikely to match native Prolog or a purpose-built rules engine.
• Look elsewhere when community support, long-term maintenance, security posture, and ecosystem maturity are hard requirements — the project's small footprint (low stars, limited adoption signals) means you should assume you may need to vendor, fork, or own the code.
• Look elsewhere when you need enterprise features (rule authoring UIs, audit trails, versioning, hot-reload, governance) — those are not provided here and would need to be built around it.
• Look elsewhere when rules can be expressed cleanly in PHP or a database-driven configuration; adding a logic language adds cognitive and operational overhead that must be justified.

How to Pitch It (Stakeholders)

• Executive summary: trismegiste/prolog is an embedded Prolog compiler and virtual machine for PHP. It would let us express certain business rules declaratively inside our Laravel application instead of as ad-hoc PHP, without introducing a separate service or vendor contract.
• Product value: Potentially faster iteration on rule-heavy features (eligibility, compliance checks, pricing logic), clearer rule ownership, and less bespoke PHP for complex conditional logic. It is best framed as a targeted capability, not a platform bet.
• Engineering value: Pure-PHP integration via Composer, runs in existing processes and queues, avoids cross-service latency and infrastructure. Fits existing deployment and testing workflows.
• Key risks to flag: Very small community and adoption (low star count, limited ecosystem), uncertain long-term maintenance, performance limits versus native Prolog or commercial rules engines, and the need for Prolog skills on the team. Assume some level of code ownership and vendor risk.
• Recommended ask: Approve a short, time-boxed spike (one or two rule-heavy use cases) to benchmark performance, integration effort, and maintainability. Proceed to production only if the spike shows clear advantage over PHP-based rules, with a documented fallback and ownership plan.